What's a podcast?

Here's a number: more than 1 billion active monthly YouTube users view podcast content of some kind on the platform. 

Aside from being another data point indicating that more and more people are getting information and entertainment through podcasts, this fact also raises the question of whether the term "podcast" brings to mind something you listen to or something you watch. Podcasts - as audio-only content - have been around for 20 years, deriving their name from a particular Apple device for listening to music and other audio content. Podcasts, as a category, were fairly niche for most of that time - the vast majority of Americans, let alone people around the world, did not listen to any podcasts. Starting in 2013, they start to trend upwards, though not at the hyperbolic or exponential rate of, say, adoption of social media platforms like Instagram or TikTok. Gradually, podcasts became part of the average American's information diet. But like social media, video streaming platforms, and every other high-choice information medium of the 21st century, podcasts offered seemingly infinite variety in terms of topics and perspectives. A few superstars dominated the podcast charts, but the distribution tail was long and listenership fragmented - most listeners never listened to the most popular podcasts. 

During the pandemic, video streaming took off, owing its popularity to the prolonged shutdown of traditional media production. It's funny/sad to look back to the early stages of the pandemic at TV producers' attempts to approximate the experiences TV viewers were used to. The dissimilarities between television (particularly live TV) and this pale imitation were striking. This moment also democratized video production in the sense that the production tools - lights, camera, set design - used by TV talk show hosts were ones readily available to regular folks. It familiarized more audiences with low/no-budget talk show production. As long as you were charismatic, good-looking, and had access to interview other charismatic, good-looking people, who cared what your background looked like, whether you were on a broadcast network, or whether or not you had a studio audience? 

I recently asked a student whether she listens to any podcasts, and after saying that she didn't, she mentioned that she was recently on a podcast (which made me wonder: what would it mean if more people were either guests or hosts of podcasts than actually listened to podcasts? Might the same have been true for blogs during their initial heyday?). At least she thought it was a podcast - she wasn't sure, because it was on YouTube and it was something you watched, not something you listened to. This should give any podcast researcher pause - make sure you understand how your study participants define the term "podcast."

I'd noticed that some of the podcasts I'd listened to on Spotify had added a video component. Of course, traditional news sources like The New York Times had been pushing reluctant writers in front of video cameras for years, since the early days of online video. The visual aspect didn't add much - it wasn't as if they edited together b-roll and interview footage, which would have meant recreating the traditional television news format on a different medium. It was just people talking - either to each other or to us. It seems to have been the rise of TikTok, Twitch streamers, and YouTube-as-first-screen among Gen-Z folks that prompted the more widespread integration of video into formerly audio or text content. Video was just a means by which to reach the large audiences already on platforms like YouTube and TikTok, not a means of adding much in terms of aesthetics or meaning.

During the pandemic boom in video streaming and podcasting, I recall realizing the importance of pre-production and editing (not live editing, as is used in sports broadcasts and other live events, but post-production editing) in the context of these shows. Those were the key separators between live streamers and podcasters, the qualities that made the former feel like an attempt to connect and converse with the audience and the latter feel like an attempt to entertain them, to put on a show. Then there were scripted podcasts like Serial or S-Town which resembled - in their production scale and in their feel - documentaries. Scripted non-fiction video podcasts - perhaps too short and informal to be called documentaries - are common, and as with their audio-only counterparts, they require more time to create than simple streaming content. Somewhere in between, you had podcasts like Freakonomics that edited scripted segments together with interview clips, something more like long-form journalism. 

But rather than written journalism, it's radio that is the obvious antecedent to podcasts. How different is the streamer directly addressing his audience for hours on end from Rush Limbaugh? How different is the group of friends joking around about news, entertainment, and one another's private lives from Howard Stern? Television talk shows - daytime and late-night - are another template. How different is an intimate podcast interview with a celebrity from Oprah? And how different might their effects be on individuals or societies?

Though there are plenty of similarities between talk radio, TV talk shows, and podcasts - enough to make scholarship on those cultural forms a must-read for anyone interested in the effects of podcasts - I can think of two important differences. The first concerns the number of podcasts - many more than were available through local or syndicated radio, through broadcast or cable TV. A lower barrier to entry means more entrants to the marketplace, and so the market for podcasts - in its scale and dynamics - is closer to the market for music: millions of creators, a few superstars, a really long tail. There might be less audience churn than with music, as audiences develop a para-social connection to podcasters and podcasts don't seem as evanescent as musical trends. 

As with any long-tail marketplace, it's a mistake to only study the distribution head (and I feel like a broken record for saying this again, but...) most listeners are not listening to whatever is trending. They're fragmented across the long tail. It's possible (even likely, I'd argue) that the thousands of niches served by millions of podcasts resemble niches served by magazines in the 20th century. Most of the niches and, collectively, most of the podcast audience consist of benign special interest content (think model train podcasts). But there's no way to know until we analyze the content along the long tail.

The size and diffuseness of the podcast market means that no single podcaster has the kind of reach that broadcasters had in the 20th century. Joe Rogan has something like 11 million listeners to each podcast while Howard Stern and Rush Limbaugh, in their heyday, had 20 million each, and that was at a time when the U.S. population was 2/3 the size, and a decent chunk of Rogan's listeners are from outside the U.S. It's worth dwelling on this point because it applies to many podcasters, streamers, and influencers. On the one hand, they have a global reach that broadcasters in the era of nationalized media markets could only dream of. But if we're trying to discern how much attention share they have (and I'd argue that attention share is a precondition to having influence), then you should be using the global population as your denominator, not the national population. In that case, no podcaster has more than 1% of the population's attention, and nearly all of them have less than .001% of it.

The second difference is regulation, or lack thereof. Howard Stern frequently butted heads with the FCC, and Rush Limbaugh had to placate the kinds of sponsors that would have likely steered clear of some of today's most popular podcasters. In the absence of FCC content regulation, edgy talk show hosts become edgier podcasters, moving their small-but-significant audiences closer to the fringes of society. Platforms regulate their content, too - creators can still get de-platformed - but it takes a lot more to get de-platformed than it took to get fined by the FCC. Meanwhile, provocateurs expand the Overton window.

But Rogan, like Stern (but perhaps not like Limbaugh), has to maintain some variety in order to maintain his large audience. Their critics tend to focus on particularly outlandish, offensive, or dangerous moments on their shows, but a quick survey of their output suggests that its not all like that, that they attempt to cater to multiple audiences. Don't like what you're hearing? Skip that episode and tune back in later. If we care about influence, we need to take into account how content varies by episode - not an impossible task so long as researchers can analyze podcast transcripts and look for keywords. 

Just as talk shows were spaces for discussion and commentary relating to social issues, political issues, and current events, so too are podcasts. Terms like "infotainment" and "soft news" can be applied to the category, though some podcasts - in format, production, and reception - are more clearly in the tradition of documentary filmmaking or journalism, and that's the genre of podcast that excites me the most. Documentaries continue to find audiences on streaming platforms, and there is no one type of documentary. It's a vibrant cultural form. Meanwhile, journalism continues its long quest for a business model to replace the one that produced a golden era of civic awareness that is swiftly receding into the past. There are a lot of people in the podcast "space" right now - audiences, creators, investors, platforms. But the medium hasn't reached maturity; it hasn't found its Orson Welles or its Dorothea Lange. For these reasons, if I were to place a bet on a means by which to tell a non-fiction story that had real impact, I'd bet on the podcast. 

Micro-blogging, Take 2

As a social media platform, you know you've achieved success when others start cloning you. It's easy to call to mind the successful copycat platforms that, in several cases, far exceeded their predecessors:  Facebook (MySpace, Friendster), Reddit (Digg). It's a bit harder to recall the many clones that never make it (Voat, Google+, Orkut), typically because the network effects that are intrinsic to platforms' success put those with small userbases at a distinct disadvantage or because they lack the infrastructure and/or revenue to support a rapidly growing userbase. In other words, there typically aren't enough people to make the place interesting or valuable, or there are too many people to keep running/moderating the platform for free. 

But Meta/Facebook/Instagram's introduction of Threads is different in this regard, giving us a chance to see what a clone could do if it didn't have to worry about those two problems. Threads has already successfully ported 100 million users from Instagram, maintaining the network structure among interest/affinity groups and connections between established influencers and their audiences. It also has Meta's massive infrastructure at its disposal - growth won't be a problem. And so we have a rare opportunity to see if this version of a micro-blogging platform - already operating at a scale similar to the existing leader, Twitter - will be all that different than what came before. 

Mark Zuckerberg has pitched Threads as a friendlier version of Twitter. Broad generalizations about the emotional valence of any social space are inherently oversimplifying - you can find pockets of friendliness and hostility among virtually any large group of people, online or offline. Still, it's entirely possible that one space could have the tendency to be friendlier than another - that's an empirically testable claim (provided you can agree on how to measure "friendliness"). 

Before trying to determine whether Threads has or is likely to achieve this goal (or whether such a goal is desirable, or if friendliness and ideological heterogeneity are mutually exclusive), it's worth considering how it might go about achieving it. Most obviously, more content moderation might tamp down overt hostility. Less obviously, there are facets of the platform that affect linkages among users - which users' posts are visible to other users. 

By importing lists of followers and popular accounts from Instagram, Threads imported a set of cultural norms, one that evolved over the last decade and privileged attractive or attention-getting still images over words, audio, or video. Broadly speaking, there's a kind of showy-ness to Instagram, a content ranking system that rewards positivity (some would argue to toxic levels). Then there's the sociotechnical context in which Threads is being deployed - as a kind of antidote to Twitter's perceived problem with negativity, conflict, and abuse. If Twitter wasn't an especially friendly place before Elon Musk took it over, it is much less so now. This might create demand for such a place, which Threads is well positioned to serve.

Then there's that pesky algorithm - the necessarily obscure formula that controls which posts appear at the top of your feed. Despite widespread skepticism toward algorithms, its hard to imagine a popular social media platform without one, particular one that aspires not to link small groups of people together (e.g., Facebook, Discord, GroupMe, and the way some people use Snapchat) but to give everyone the chance - however remote - to command an audience. Imagine ranking YouTube or TikTok videos chronologically, or at random. Some weighted combination or popularity, engagement (e.g., number of comments or shares), and predicted affinity (amount of time you've spent on similar posts) is the best way to keep users coming back for more. 

One way to go about ranking posts is to defer to the masses - showcase whatever is broadly popular, as Twitter does with its prominently displayed list of trending topics. Another way is to tailor it to each user's preferences - the niche approach favored by TikTok. The first kind of ranking creates a "main character of the day" a target for attention and ridicule on and beyond the platform. The second kind, supposedly, creates echo chambers (though evidence is mounting that, as intuitive as this understanding of personalized ranking is, it doesn't fit what most users actually see on social media). Inheriting its structure from Instagram, Threads seems to privilege, as Kyle Chayka put it, banal celebrities and self-branding. As masspersonal media where any user can potentially reach millions of other users, Threads cannot help but encourage a kind of performativity over connecting with a small group. 

Then there's the shift from images and short video to text. The whole reason Threads is being talked about as a Twitter clone is because its primarily intended to be used for mass conversation. In their branching/nested structure (you can reply to a reply to a post, with each reply "nested" under the previous message), conversations on Threads resemble conversations on Reddit, and it will be interesting to see if future designs of Threads nudge users to engage more in the replies.

But I wonder about the brevity of text and what that does to conversations. The whole point of Twitter - what put the "micro" in "micro-blogging" - was the character limit (originally 140, upped to 280). It's well-suited to a fragmented attention universe, but I wonder if the tone of Twitter (witty, sure, but also mean) is an inevitable symptom of its mandatory brevity. Is there something about short-form writing that is bound to regress toward snark? Is that simply the nature of the medium, regardless of the combination of people and level of moderation? That's what Threads might give us a chance to observe.

The promise and threat of A.I. in creative domains

Though we've been expecting AI to get good enough at writing to actually perform a decent number and variety of writing tasks "by itself" (it still needs humans to engineer prompts), we hadn't been confronted with that reality until recently, when ChatGPT became more widely used. To test it out, I gave it some of the (relatively simple) prompts I give my undergraduate film history students and saw what it came up with. Then, I asked it to write a pilot episode of a teen drama set in Montana, a grant proposal for a research study on social media use and political polarization, a research paper on the environmental impact of microplastics, a quiz on 1970's media cultural studies, a review of Beck's new album, an amicus brief on microplastics, and a summary of the 1998 NBA Finals in the style of Proust. The results, as many have noted, aren't perfect but are a lot closer to perfect than what we're used to seeing from programs. It's hard to objectively convey the quality of the output and the limitations of the tool; it's best to just try it out yourself. 

I'm sure such tools will improve, but it's hard to say at what rate and to what degree, so I'll try to just stick to evaluating the impact of the current iteration of generative text programs like ChatGPT on two facets of writing: assessment (specifically, educators' ability to assess students' understanding of concepts, thinking, and communication skills) and its applications in various domains (i.e., journalism, creative writing, scientific writing). 

In terms of assessment, the ability of students to avoid actually doing the work of writing for an assignment and to avoid detection has increased significantly. However, the truth of this statement is highly dependent on the assignment. If the assignment just requires students to gather information (particularly older info on an extensively covered topic, person, or event) and synthesize it into a simple, readable essay or article, then ChatGPT seems to be quite good at that. But what about, say, watching a particular video on YouTube and applying something from a particular reading to that video? I would assume that ChatGPT can't easily extract the information that's in the video, so it would have a tough time with this task, and that it's ability to do anything with a particular reading is contingent upon that reading being freely available and accessible online somewhere. If the reading is in a textbook that doesn't appear online (or only appears on a few hard-to-access pirating sites), then this will be harder for ChatGPT to work with than, say, the Magna Carta or any other text that's in the public domain. But in any of these cases, I think that A.I. co-authoring (where ChatGPT does some of the work and the student changes and adds a few things) will be essentially impossible to detect. 

Another approach to ChatGPT's threat to assessment is to simply proctor writing assignments. That's easier to do for short writing assignments but difficult for longer ones, and impractical for online classes. Still, as a professor who has an interest in fairly and accurately assessing his student's writing, I'm leaning toward more in-class writing assignments and fewer outside-of-class writing assignments because of how challenging it will be to tell the difference between A.I.-generated writing and my students' writing outside the classroom. 

But the topic of applications of AI is more interesting to me, and in some sense pre-empts questions about assessment. If AI can accomplish much of what we're trying to train our students to accomplish, what is the point of such training? The rapid adoption of ChatGPT has forced me to reconsider the relationship between writing and thinking. Writing is often the medium through which thought is expressed, though not the only one; spontaneous discussions and conversation are a good alternative. When is writing chiefly a vehicle for thought and when is it more an integral part of the process of thought? Those who defend the sanctity of human writing, I surmise, would say either that writing is very often part of thinking, or that we may not be very good at being able to tell the difference between writing-as-vehicle-for-thought and writing-as-thinking. Therefore, ceding the task of any but the most formulaic types of writing to AI risks sacrificing the ability to think. 

We still want to get better at thinking, and we still want our students to get better at thinking (e.g., critical thinking, creative thinking, logical reasoning, problem solving). Even in a world of prevalent AI, having those abilities will make us better at prompt engineering, better at judging the value of what ChatGPT and similar AI spit out, and better at making refinements to that output. The same would apply for non-linguistic AI: prompting an AI architectural design program and judging/refining the results; prompting an AI coding program and judging/refining the results. In any application I can think of, humans are still part of the process. Whether AI is producing a kind of structural scaffold for ideas, identifying sources of information, or generating new ideas, it has to be set in motion, its output needs to be evaluated, and in its current iteration, its output requires a fair amount of refinement. That process of prompting and refining can be similar to a good conversation or collaborative improvisation ("yes, and..." thinking). 

I sense that there's a widespread antipathy toward applying AI in creative domains. I don't consider myself an AI optimist. I acknowledge how tempting it will be for students, businesses, creators, and governments to use AI in an indiscriminate manner, not bothering to vet or refine its output. I acknowledge that such use could cultivate a kind of passivity and (further) overreliance on technology. More people would get out of the habit of "thinking for themselves." Creativity would be increasingly derivative in the name of efficiency. 

But does this warrant an outright ban on AI? What would such an approach sacrifice?

I feel as though we've been good at articulating the risks of AI (aside from the aforementioned, there's scaling up spam and disinformation, and deceiving job recruiters or potential partners on dating sites). We're less good at articulating its potential upside. I think of that upside chiefly in terms of resource reallocation (which, yes, sounds very cold and business-speaky, but hear me out). 

Let's treat ChatGPT and the like as co-authors. They generate first drafts or templates but don't write the entire text or finished product. Human writers' role in the creative process shifts from crafting sentences and paragraphs to gathering primary original sources and identifying needs in their audiences and communities. What if writers could take the time they would have spent struggling to write formulaic copy and instead spent it cultivating twice as many primary sources as they would have otherwise, or co-writing twice as many stories, or ten times as many stories? Consider all the un-written stories or accounts of events; consider what's missing from historical accounts and news coverage, in part because the people who know how to create thorough and entertaining writing only have so much time. Some people's stories are told, some people and events are remembered, but the vast majority are forgotten. What if we could fill in some of those blanks? We don't have to be indiscriminate in our use of AI to turn data into stories that no one cares to read. Remember, humans and their understanding of what is valued are still part of the process. And what if we could offer those stories in twice as many accessible formats? If editors and readers valued these qualities more than they feared AI's downsides, we could use AI to improve our information environment. 

The genie is out of the bottle. If one country or group of people wants to spend time trying to stuff the genie back into the bottle, that won't stop other countries or groups of people from using it. We needn't be totalizing in how we conceive of the application of AI in creative domains. We have been discriminate in our use of technologies in the past, often making mistakes, attempting to correct those mistakes by introducing limitations or redesigning the technology, fitfully moving along but rarely un-inventing anything. Maybe we should look around and see where the successes and failures are right now. 

Futures of Twitter: Scenario Testing

Yes, I've railed against the appetite for future forecasting in this blog before. In fact, pretty much every post from the past few years is, in its own way, a screed against the kind of prediction of complex systems of long periods of time that news readers and journalists who interview academics can't seem to get enough of. And yet, when something "big" happens - a pandemic, the election of Donald Trump, Elon Musk taking over Twitter - I feel the same insatiable pull toward forecasting that everyone else feels. These are important events with far-reaching implications, and so despite their complexity, we can't seem to just say, "who knows what will happen!" We have to venture a guess.

And not just any guess. When we see worst-case-scenarios as plausible, we detest a future in which we ignored the threat so much that we have to predict doom. The unpleasantness of comprehending those futures is outweighed by our fear of feeling guilty about (and of being guilty of) not having done enough to prevent them. The other side of the argument is that there has never been a time in human history when worst-case-scenarios weren't plausible, and to spend time constantly ringing alarms is both joyless and unproductive, and that our inability or unwillingness to recall the false alarms of yesterday keeps us from learning anything about how complex systems actually work, to actually improve our prediction accuracy, and - by extension - to improve our world. I do get both sides of that argument, and so to me it seems unresolvable. 

So, to further refine my stance against long-term predictions about complex systems (the global economy, geopolitics, culture, developments in technology, etc.), I'll say that I prefer something less like predicting whether some event will spell doom for society (super vague, no timeline for when "doom" will occur, what shape it will take, etc., and so unfalsifiable) and more like fivethirtyeight's scenario testing. You start with several plausible scenarios - each one mutually exclusive to the degree that it's possible, and fairly specific about outcomes and timelines but not so specific as to be inevitably falsified by some minor quirk of history. This, at least, would allow us to learn something if our predictions are wrong, allow us to do a post-mortem and see what we missed, what variables we weighed too heavily, etc. Of course, this is dissatisfying if you are a doom-predictor because all the learning in the world won't amount to a hill of beans after the apocalypse that you failed to predict! But assuming there's at least a few people left on planet Earth, learning will be a good thing. To my mind, entertaining somewhat optimistic scenarios isn't mutually exclusive with being prepared for (though not actually predicting) the worst. 

In that spirit, here are a few scenarios regarding Musk's takeover of Twitter, some more optimistic than others. They use three metrics of success/failure: financial success (does the company turn a profit, stay solvent, continue to exist), cultural relevance (does the general public care about what's said on Twitter as much as they do now, more than they do now, or less than they do now? Does some other platform become the proxy for vox populi that Twitter is right now?), and "externalities" (affective polarization, political violence, political revolutions, cancelling/calling out people. Externalities could be both "good" [revolts against dictatorships, publicly shaming those who deserve it] or "bad" [downfalls of democracies, publicly shaming those who don't deserve it]).

Scenario 1: Financial success with lower cultural relevance and few "externalities." The most intriguing part of Musk's takeover to me, so far, is his apparent willingness to blow up the existing way that Twitter makes (or attempts to make) money. Perhaps the changes he instates drive user count WAY down, but this won't necessarily make Twitter less of a financial success. He could charge a portion of users $8, or pay the 100 most followed $1,000,000 and charge anyone who tweets more than 100 times a year $50 (a kind of 'lottery-ticket' model that, when you think about it, isn't that different than would-be filmmakers shelling out for expensive equipment and film school for a crack at a studio contract). My personal favorite idea is Willy Staley's "congestion pricing" plan - when a certain number of users have tweeted about a topic, the price of tweeting about it increases, which would - in theory - encourage people to tweet less about trending topics and more about a diverse array of topics. Or maybe a revived Vine drives profits and allows Twitter to continue to be a loss leader. Regardless of how he does it, it's possible that Twitter becomes profitable.

Meanwhile, the platform loses some of its cultural cache. The behavior (on Twitter and off) of Musk and a handful of high-profile Twitter users who would have been regulated under the old regime turns off journalists and tastemakers to such a degree that they stop paying attention to it (regardless of how outlandish it is) and pay more attention to how YouTubers, TikTokkers, and podcasters react to the day's events. Twitter will always have the brevity and "portability" of text on its side - it's easier, in the course of conversation, to tell someone what another person Tweeted than to try to describe even a short video. So, maybe a Twitter alternative (short text, highlighting trending topics) pops up and steals at least part of the cultural spotlight from Twitter. 

Regarding "externalities," there's no convincing evidence that what people say on Twitter causes political violence, revolutions, voter intimidation, cancelling, etc. These things happened before and they continue to happen, but it's just as easy to point to what people are saying on TikTok, YouTube, and podcasts as it is to point to what people are saying on Twitter as the cause of it, and so the argument that a Musk-led Twitter is leading to the downfall of society never really gains traction. 

Scenario 2: Financial success with the same level of cultural relevance and no apparent increase in externalities. Same as Scenario 1 except people (journalists, podcasters, YouTubers, TikTokkers, and - by extension - people who pay attention to what those people have to say) keep paying attention to Twitter. Maybe what's said on Twitter doesn't change all that much, or maybe it turns into a different kind of dumpster fire that people can't ignore. This is basically a kind of 'status quo' scenario. Sure, somethings change (the way Twitter monetizes users, the number of users, the character of the userbase), but no seismic changes to culture or to Twitter as a corporate entity. To me, this still feels like the most likely scenario. Habit and inertia are powerful forces - people will want to keep using the platform they've gotten into the habit of using, and reporters will want to keep referring to Twitter as vox populi. The bulk of everyday users who don't engage with trending topics will muddle along - perhaps as long as they have no interest in reaching large audiences with their tweets, they'll be allowed to use the platform for free. 

Scenario 3: Financial success with the same level of cultural relevance and "bad" externalities. In this scenario, there are a few instances of political violence that can be clearly and obviously linked to what people say on Twitter. Musk will point out that people are saying the exact same things on other platforms like YouTube and TikTok and that his company is being judged by a double-standard, but the sizable portion that already has it in for him won't want to hear it. On a "normal" ad-supported social media platform, this would start a death spiral - advertisers pull out, revenue craters, and they can't keep the lights on. But it's interesting to consider what would happen if Musk pivoted away from an ad-supported model, which he already seems to be doing. How bad and/or obvious would the externalities have to get before governments blocked the platform? I suppose middle-layer companies (occupying the space between users and platforms) like Apple, Alphabet, and AT&T might say 'enough is enough' and drop Twitter, but then maybe Musk uses Starlink to do an end run around them! This sounds a bit far-fetched to me, but you never know. 

Scenario 4: Financial failure. Enough high-profile Twitter users leave that the platform becomes less attractive to many everyday users, and the ad-supported models becomes unviable. Musk's attempts to charge subscription fees results in users trying to circumvent the fees, leading to draconion crack-downs, further turning off everyday users who head over to YouTube, TikTok, podcasts, Reddit, and Twitter clones. It's odd to think of a platform that still has cultural cache going belly up, but to some extent this is what happened to Vine. If you can't make the numbers work, your impact on culture is a moot point - you just cease to exist...or you get acquired, sold off, merged, etc. What might Twitter's afterlife look like if that happens? 

This, I think, gets us to focus on particular observables - financials, number of users, the extent to which people are talking about/paying attention to what's said on Twitter, political disruption - which is all I'm really hoping for in conversations about the future. 

How platform-specific is influence?

In the past, I've railed against making predictions about the future as a way to understand the present. This is different than predictions used as a way of dealing with uncertainty through humor - a pretty common, totally understandable reaction to crises. I'm thinking more of op-ed hot takes that seem to want to be taken seriously.

Predictions like this are often so vague that they're impossible to prove wrong. For example, if I predict that Twitter/Facebook/Reddit will die/fail, how and when will I know if this turns out to be true? If their userbases, sometime over the next 5 years, decline by 35%, have they died/failed? How about 50%? Do we have to wait another 5 years to judge the prophecy? There's also the problem of lacking a counterfactual. If something horrible happens after someone uses social media, we can't compare it to a world in which they did not use social media. It's possible the horrible thing would have happened anyway (or perhaps something even...horribler?), just through some other mechanism. There is no disincentive for continuing to make bold, wrong predictions because there is no mechanism for keeping score, no highly visible public record of wrong takes (though spectacularly wrong takes do tend to catch flak).

And yet I'm finding it hard not to use the occasion of Elon Musk's (apparently successful?) attempt to buy Twitter as a time to indulge in some predictions. I'll compensate for this indulgence by offering something more in the spirit of this blog - using the occasion as a way to gain insight into something more general about the uses and impact of social media. But first...

I can think of two likely scenarios:

Scenario 1: very little changes. Twitter use habits, like any kind of habit, are hard to change. There have been many instances in which social media platforms have done something that users have not liked, but most users do not then abandon the platform. We can more easily recall the instances in which they did abandon the platform: MySpace and Digg come to mind for me. But it seems that nearly every significant change to a platform - be it functionality, moderation policy, or ownership - tends not to result in a wholesale change in user behavior. The "culture" of Twitter may change, but linking this to Musk's ownership can be a tricky claim to verify, as cultures are always changing. In this scenario, there is no massive change in Twitter discourse (i.e., who participates and what is said or amplified) that can be directly and obviously linked to Musk's ownership of the platform. A handful of influential Twitter users on the Left will defect, as will a few hundred thousand less-influential users (including many journalists who will write about the experience). They will be displaced by a few newly influential users on the Right and a few hundred thousand less-influential tech bros and Far Right/Alt Right users. Musk might put the worst of the Far Right users in seemingly random "time outs," less out of any political conviction and more to reassert dominance get a laugh at their righteous indignation at having their trust betrayed. Losing the revenue they generate through ad exposure or subscriptions won't hurt, but the board will chastise him for playing fast and loose and he'll promise to be better. Pundits will pin everything the Right does on Musk and Twitter, but the connection won't be obvious and the claims won't be of interest to anyone outside of a bubble of journalists, news junkies, and academics. I consider this the more likely of the two scenarios. 

Scenario 2: things go poorly, less because of how Musk changes the functioning of the site and more because of the signal it sends to current and potential users. Far Right fringe groups and apolitical trolls will see Musk's unwillingness to regulate content as an invitation to push things as far as they can, inciting small-but-significant numbers of Far Right "activists" to engage in terrorism and assassination. A handful of violent political acts will be linked to Twitter in a way that will seem obvious and undeniable, not just to readers of New York Times opinion pieces but to the average politically-disengaged citizen, who will come to associate Musk and all his brands (e.g., Tesla, SpaceX) with toxicity rather than innovation. Musk will then belatedly recognize the damage to his brands and sell the company. 

So as to make these scenarios more falsifiable, I'll say that one will happen by the end of 2023. 

With that out of the way, I'll return to the title of the blog post, returning to a topic that I'd like to write about at greater length in the future: what is the nature of influence on social media platforms, and how does it differ (in duration, scope, domain-specificity, etc.) from mass media or face-to-face influence?

In thinking about the possibility of influential Twitter users defecting to another platform, I realized that platform-abandonment might involve losing one's audience and the attendant influence. All fine and well to say "follow me to YouTube/TikTok/Substack/Tumblr/Medium/Mastadon/whatever!", but it's hard to coordinate a mass exodus to another platform, and harder still to sustain that interest over time, especially when the new content home offers more of an a la carte content experience rather than the smorgasbord we've come to expect from popular platforms. Smaller platforms have trouble handling large influxes of digital refugees. Perhaps especially high-profile influencers will easily move their following to another platform (or to podcasting), but what of the Twitter users with followings of 500 to 50,000? How portable is their influence? 

Those who jump ship may lose some of their audience but find a more intimate relationship between themselves and a smaller group of followers on another platform, and this may be more rewarding for them. Those who stick around a less-regulated Twitter may find themselves in more direct battles with other users with whom they disagree than had previously been the case. The 'block' function and tweaks to the much-discussed-but-poorly-understood algorithms will help determine how easy it is for users to tolerate dissent in the name of maintaining influence. But no matter how it shakes out, I think we can learn something about influence by seeing what happens to the public personae of Twitter users with decent-sized followings who leave Twitter. Maybe Twitter's loss will be YouTube's/TikTok's/Substack's/Tumblr's/Reddit's gain, both in terms of users and in terms of cultural influence, however one chooses to define and measure that slippery concept.  

‘The Curdling of the Internet’: The Open Public Sphere Internet as Threat Amplifier

A weekend retreat to a cabin in the woods provided me with time to finally get around to reading Jia Tolentino’s essay, ‘The I in the Internet.’ In a way, I’ve been thinking about what Tolentino describes as the ‘curdling’ of the internet for the past two years, since our research team started reviewing research on various forms of online hostility. More broadly, I’ve been thinking about the effects of social media on societies for the past decade.

I’m generally opposed to sweeping pronouncements about the negative effects of the internet, smartphones, or social media, mostly because it doesn’t seem to fit the evidence. Social media use, by itself, doesn’t seem to have much of an effect on well-being or depression; that is, if one person spends three hours a day on social media and the other spends one hour, or no hours, the person who uses more social media is no more likely to feel bad about themselves or about life in general. There’s also evidence that the internet exposes users to a wider range of opinions, rather than sorting users into filter bubbles or extreme echo chambers. Bad things may be happening in today’s world, and social media use might have increased at the same time, but that doesn’t mean that one caused the other to occur.

And yet, despite the apparent lack of evidence of a strong, negative effect of social media use on individuals, I can’t help but wonder if we, as researchers, are missing something, and how we might adjust so as to capture those things.

One way Tolentino’s feeling and the lack of individual, direct effects on social media users can both be true is if the internet/smartphones/social media are having a profoundly negative effect on society in general, but it occurs in some kind of indirect way. The most concise way of describing my hunch about this would be the ‘threat amplification’ effect. These technologies amplify certain voices, making certain kinds of people and behavior that were formerly invisible more visible. A sub-set of highly active social media users see the platforms as battlefields on which an ideological war is being fought, and so they post information that furthers their agendas, and/or a subset of especially passionate people simply express how strongly they feel about some issue. These expressions are perceived as threatening by a sub-set of other users, not necessarily because they contain explicit threats of violence, but maybe because they clash with some fundamental belief of theirs, or portend an escalation in the encroachment on their rights (e.g., the right to free speech; the right to exist; the right to defend themselves). These posts stick out to many people, draw attention to themselves in the way that any perceived threat in our environment sticks out to us. If future visibility of posts is determined through the amount of attention paid to them (via algorithms or 'most read' lists, etc.), then we tend to see more and more of these types of posts as time goes on.

Also, well-meaning users (journalists, re-tweeters, etc.) draw further attention to these posts in an effort to make sure that others see the threat because to ignore the threat would be hazardous. They might do so out of a sense of duty and compassion to others (i.e., they see others are in danger from the threat and must warn them) but might also do so out of self-interest, or in-group-interest. By drawing otherwise apathetic individuals’ attention to the threat, they may enlist them to join their fight. In such a way, much of the online discourse comes to resemble either a threat or a response to a threat.  

If we react to this by leaving the internet, by not participating, this may preserve our piece of mind, but it cedes the public forum of the internet to those holding more extreme views. So, perhaps we try to meet the threat with an equal and opposite assertion of our beliefs or values (which may, of course, be viewed by others as extreme and threatening). Or perhaps we just conform to the now-established norm of value-assertion-through-strong-takes in order to be heard (because in order to gain greater visibility in the form of likes, shares, and subscribers, it helps to conform to norms of what is popular), or simply because humans are prone to unconsciously conform to social norms of expression. All of these would lead to an internet that actually is becoming more threatening (again, defining 'threats' not in terms of what was intended, but how they are perceived by someone), and exposure to it would likely lead to increased polarization, depression, abuse, harassment, toxicity, etc. The internet may not have started out that way, but it could be the case that it is becoming that.

And that’s the tricky part. The internet that Robert Kraut analyzed 20 years ago in his landmark study of the effects of internet use had certain kinds of content and certain kinds of experiences and perspectives posted by users, and the internet that the research summed up in Hancock et al. has other content/experiences/perspectives, and today’s/tomorrows internet has/will have other content/experiences/perspectives. And if those three stages of the internet are sufficiently different from one another in terms of their contents, they may have very different effects. Thus, though we haven’t observed strong negative consequences of social media use, it’s impossible to rule out them occurring in the future, or right now, given the publishing lag and, perhaps, that we're looking at the wrong outcome variables.

The negative effects of internet use may not be depression, narcissism, or physical aggression. They may manifest themselves in voting behavior (e.g., voting for increasingly partisan, extreme candidates, so as to counter the perceived threat from the other side), or some other behavior that reflects a distrust in others (e.g., unwillingness to live in certain places or send one’s kids to schools with certain types of people, a kind of self-segregation). Eventually, this kind of mutual distrust may manifest itself in physical violence. Or perhaps we’ll view one another as very, very different and threatening, but ultimately leave one another alone, co-existing peacefully if not without mutual resentment (stranger things have happened).

But here’s an important limitation: everything I’ve called ‘the internet’ up until this point really refers to part of the internet: the open ‘public sphere’ internet: Twitter, Reddit, comments sections on news websites, the part of YouTube in which YouTubers engage in a kind of running commentary about the world; maybe certain users on Facebook and Instagram who use those platforms in this way. Tolentino does note that she's mostly talking about the 'social internet.' This is the part of the internet in which a single individual can post something that reaches many other individuals (one-to-many). But many of Tolentino's observations also seem to apply to news online, which is tightly linked to Twitter (the bubble that journalists live in is the bubble of the open public sphere internet). It’s worth remembering that the internet is a lot more than just this. It is Netflix and other streaming services: ‘top-down’ platforms in which content is created by a small group of professionals and consumed by a large audience. It is small-group communication via messaging apps (one-to-one, or several-to-several). Tolentino’s observations about online hostility probably don’t fit as well to small group communication online (which is 'social' and is online, though maybe it's pedantic to call it part of the 'social internet), and they only apply to Netflix and other mass media insofar as they try to reflect the zeitgeist of the open public sphere internet.   

The Open Public Sphere Internet as Difference Revealer

Now that there are so many people participating in public discourse online, the open public sphere internet has exposed groups to one another that are so unlike one another to begin with, in terms of their values, experiences, and perspectives, that independent of how aggressive or antagonistic they are, this difference is so shocking and threatening that people get freaked out. That is, it isn’t necessary to have people act in a hostile way toward another group, or in a strategic way so as to counter the messaging of others. Merely by expressing themselves, by showing who they are and what they believe, they may set others off.

Human difference was depicted and conceived in a certain way by mass media. It was often visual, concise, and fictional. So yes, traditional/legacy media depicted difference, but in a circumscribed way, made generic through the use of tropes and bracketed as fiction. While we weren’t consuming images of difference via mass media, we spent our time around people who are not terribly different in terms of beliefs, values, and experiences. We spent a lot of time around family, friends, schoolmates, and workmates. If we were out of sync in our beliefs or values, we often avoided those subjects in order to avoid conflict.

The differences that we see online are differences in values being expressed. Those differences always existed (there were always people who believed something that you would have found abhorrent), but we didn’t have to see them every day. We probably were never going to be particularly good at reacting to these differences. Many of us probably always would have perceived them as a threat to our own values. So, it could be argued that the internet is the first technology, the first moment in history, where we really have been confronted with values differences as they have always been. Of course, these online expressions are not pure reflections of any group's beliefs, are manipulated in various ways (though when we’re quickly scanning a feed and clicking on links, we may not recognize this). Nevertheless, despite the fact that they are not representative of the larger group, they are expressions of the beliefs and values of many real people. And maybe we feel this when we go online; we feel how real they are. They are not fictional characters dreamed up by a screenwriter. These are actual people who actually believe the exact opposite of what we believe.

It’s not surprising that people feel threatened by those differences. And so many folks react to the threat with a kind of siege mentality, and then many subsequent cultural expressions and public life become a reflection of that. And the only alternatives seem to be to carve out small clusters within online life via group messaging apps or forsake social media entirely.

What impact does the curdling of the open public sphere internet have on the world?

Why does any of this matter? Is it just a bunch of people bickering in cyberspace or does it have some clear connection to the rest of civic life? If some of us decide ‘to hell with it’ and only use social media for small-group communication and leave Twitter to the trolls, what would it matter?

I do wonder if the relationship between what is said on the open public sphere internet and power (political power, economic power) could change, or is changing. Perhaps when the open public sphere first became widely used in the United States, most people, including journalists and politicians, saw it as a kind of proxy for public opinion, overlooking the fact that only certain types of people expressed themselves. The apparent connection between what went on in the run-up to the 2016 election (expressions of extreme partisanship, particularly an insurgent group of Trump supporters engaging in a kind of online battle on behalf of their chosen candidate) and the outcome of that election (the election of that candidate) supports this view. 

But what if, in the coming months, the same open public sphere internet were to heap praise on Bernie Sanders and Elizabeth Warren while continuing to deride Donald Trump and deriding or ignoring Joe Biden, and Biden or Trump end up winning the election? What if that inconsistency between opinion on the open public sphere internet and a democratic election outcome were to happen a few more times in high-profile elections in different democracies? Many people might come to believe that opinion on, say, Twitter, neither reflects nor causes shifts in larger public opinion. Once this is acknowledged, I do wonder if at least some people, either in the general public or in positions of power (e.g., widely-read journalists), would be less likely to take their cues from opinion expressed on the open public sphere internet.

There’s a bit of a self-fulfilling prophecy aspect to it, I think. When people believe that Twitter is a bellweather, they look to Twitter and are subsequently influenced by opinion on Twitter. The evidence on which they initially base their belief that it is a bellweather might be suspect, but that doesn’t matter: once they believe it, they essentially bring it into being by assuming that it is public opinion writ large, are influenced by it as such, and, through their writing, influence others. That is, opinion leaders see a popular trend on Twitter and write about it as though it were popular more broadly. Others take cues from the opinion leaders and act on that information, turning it into a truly popular opinion. However, if opinion leaders stopped believing this (and again, it wouldn’t matter whether the reason they stopped believing it made much sense or was supported by evidence), they might ignore it and thus Twitter and the like would lose its power to influence public opinion writ large.

Maybe people in a certain social stratum are already leaning this way, avoiding social media (or at least the open public sphere internet) themselves, raising their kids to avoid it as well. These people are often quite powerful: upper class, working in tech, politically active. If they start ignoring opinion as expressed on the open public sphere internet, I can imagine all of it becoming like certain comment sections of certain news websites: it exists, it is ugly, but most readers simply ignore it, and it doesn’t really have much of an impact outside of itself.

In any case, it’s important to not simply assume that the open public sphere internet has a stable relationship with public opinion in general. I think it’s also worth thinking about the popularization of the open public sphere internet as the first moment in human history that we saw how different our views of the world really are, how directly they conflict with one another (there is also much agreement, though the current iteration of the open public sphere internet doesn’t seem suited to highlight that). It’s hard to imagine such a moment going smoothly. But perhaps it’s a matter of getting over the initial collective shock of it. Or perhaps we just need a little time to ourselves.

A World Without Frames

I had the privilege of seeing Jimmy Wales, founder of Wikipedia, speak at the University of Alabama, courtesy of The Blackburn Institute. In anticipation of seeing him speak, I'd been reflecting on the value of Wikipedia in a post-2016 world. Since the 2016 U.S. Presidential election, it seems as though the discourse on social media has become more toxic and less fact-based, that traditional news outlets don't quite know what to do with Trump and his international equivalents, and that non-traditional news outlets are creating and disseminating biased and false information about our world. All the while, Wikipedia continues to churn away, largely free from the toxicity and contentiousness that has gripped the rest of the internet and, seemingly, the rest of the world. How did they do it?

I went into the talk with a slightly more specific version of that question: is it the particular approach/model that Wikipedia uses that is responsible for its relative success vis a vis the Truth, or is it the particular domain in which it operates - that of the encyclopedia? Wales didn't quite speak to this question, but he did talk about his relatively new passion project: the WikiTribune. In a way, the fate of that venture will answer the question, as it applies the model and logic of Wikipedia to the world of news and current events. Wales' working theory seemed to be that ads were largely to blame for the degradation of news: the way that the online ad economy works puts all websites on an even playing field, all competing against one another for attention. News sites do not just compete with other news sites; they compete with parody news sites, entertainment sites, gossip sites, etc. He praised the recent move toward the subscription model, noting that the New York Times has seen recent financial success pursuing this model. Subscriptions prompt users to think, 'what is the overall value of this product, in the long term?' That's a key shift in thinking, from what you click on in an impulsive manner to what you value, a shift from short term thinking to long term thinking. So, if we get rid of the ads, do we improve the quality of news and discourse around news?

My suspicion is that there is another factor at play: whether the content pertains exclusively to current events. News must privilege certain stories over others in a way that an encyclopedia or a library does not, assuming it has a front page (can we conceive of a news site without a front page, regardless of whether said front page is personalized?). Here, the decades of research on framing and agenda setting is relevant: by virtue of editorial decisions about what to cover and what not to cover, news gets us to think about certain issues or events (or certain aspects of those issues/events) and ignore others. Encyclopedias do not direct attention in quite the same way. Sure, it could be argued that within a given entry, an encyclopedia/wikipedia chooses to emphasize certain aspects of the subject while ignoring or downplaying others, and thus frames the subject in a way that shapes perception. But I'd argue the way in which Wikipedia has incorporated different perspectives on contentious topics into entries reduces this effect.

Can you do the same thing with news? Is that what WikiTribune will be?

I haven't a clue. But it was kind of thrilling to be in the room with someone who was taking a stab at solving a problem of this scope, someone who was uniquely positioned to stand a decent chance of succeeding.

White Flight Part 2: When the upper class disconnects

It's been awhile since I've published anything in this blog. Mostly, it's been the incentive to publish in peer-reviewed journals in order to attain tenure that's to blame for the lack of blog productivity. I continue to have stray, undeveloped thoughts about media uses and effects, and there are a few drafts of blogs waiting to be finished, but in the meantime, here's one that's been percolating of late.

There are reports from the past year that many highly-educated, upper-class or upper-middle-class parents are raising their kids with minimal or no screen time, primarily out of fear of its addictive qualities. It seems to start with lay theories of people who work in the tech industry and/or people who live in Silicon Valley - people with a very idiosyncratic perspective on media technologies. One could look at this particular group of parents as experts, given their unusual access to the ways in which these technologies are developed, marketed, and used. But it's also possible that their experience skews their perception of the extent to which these technologies actually are addicting or otherwise pernicious.

One possibility is that the parents are right, that the technologies are pernicious, at least when used in what they deem to be excess. Another possibility is that they're mistaken, that the technologies are merely a new form of communication, like books or telephones, not bad in and of themselves. For now, I want to set aside that issue and focus on the repercussions of a certain type of young person - an upper-class young person - dropping out of the social media universe (or never participating in it in the first place).

There might be a new kind of digital divide, one in which upper-class young people are not participating in or contributing to online social spaces. Those young people will, of course, communicate with one another, through face-to-face social networks if not through technologies that upper-class parents look at with less fear (the good ol' fashioned phone; Facetime/Skype; maybe even texting). They'll use the internet, of course, but primarily for work, or the consumption of curated content with high production values.

Meanwhile, the hurly-burly social media universe - the YouTubers, the memes, the bullying and the overnight fame, the narcissism, confessions, and anonymous social support, all overcrowded with ads - will continue to exist. If the hostility and hate speech get worse and worse, and if other people become helplessly addicted to its pleasures? Well, that's their problem. It's hard not to think of the 'white flight' of privileged families from the sites of fear and anger of yesteryear - urban centers. Privileged young people's image of the unruly social media universe will be akin to the caricature of urban life that children of the 80's grew up with: they will see the most sensational worst-of-the-worst stories, and have no personal experience with it to temper these simplistic, negative depictions. When they get to college, whether or not they grew up on the internet could be as important as whether they grew up in a one-stoplight Midwestern hamlet or Brooklyn. The social distance between a lower-middle class child who spent hours on social media from age 9 and an upper class child who read books and played Dungeons and Dragons at his friend's house, even if those two kids grew up across the street from one another, might be immense.

Among the many fears that social media evoke is the fear of the filter bubble: that subtle social media algorithms and quirks of human behavior will work to balkanize societies. Ten years after the popularization of social media, evidence seems to suggest that the opposite has happened, that we vastly overestimated the power of those algorithms, underestimated the extent to which offline social networks of old were already balkanized, and underestimated the serendipity and unpredictability of evolving online social networks. If balkanization occurred, and if it is occurring again, it may be between those who were/are socializing online and those who were not/are not.

What Does Everyday Media Use Look Like? (and why this might bias our perception of digital media's effects)

Two brief anecdotes:

1: I’m sitting in Railroad Park in Birmingham, enjoying a breezy, temperate Saturday morning. A few folks pose for a photo that someone else takes with a smartphone. I guess I notice these people first in part because I cannot take a picture with my smartphone - the camera in it is broken. There is nothing like being robbed of something that you have taken for granted to get you to notice it more and to think about it more. I see a few other people in the park typing messages on their smartphones. Other people talk to one another face-to-face. Others stand around and take in the landscape, pet other people’s dogs, read a magazine or a book. And here I sit, typing on a laptop. What do we look like to each other? What kinds of assumptions might we be making about each other based on what we're doing in a public place with or without media technologies?

2: I'm enjoying a beer and a musical performance at Band of Brothers, a new brewery here in Tuscaloosa. The beer, the music, and the general vibe are all great. At the end of the performance, the lead singer, an elegant, attractive, charismatic young woman sits down at a table near the stage, gets out her smartphone, and seems to instantly transform herself into a zombie, hunched over a tiny screen that illuminates her dead-eyed stare.

It isn't hard to find people who are concerned about excessive media technology use (in particular excessive smartphone use). The most popular books about digital media use and the most popular articles take a pretty dim view of it. If there was a utopic moment in the history of such technologies, that moment seems to have passed. This recent commercial for Cisco feels like a relic of a time before we became so deeply suspicious of digital media (perhaps it's a response to that suspicion. Why else would we need a "pep talk" about the virtues of technology?). 

Where do we get these ideas about media use? Or: why are we so keen to agree with, and so reluctant to question, those who provide anecdotal evidence of its ill effects?

Often times, we are heavily influenced by our direct observations: we look at the people around us, the students in our classes, the family members at our cookouts, the friends at parties, the kids at our friends' houses, and the people in the park. Direct observation informs our intuition, and we seek out confirmation of that intuition in the books, blogs, articles, and documentaries we consume.

I've been thinking about how the relationship between our typical first-hand observations of media use and the actual fact of media use (regardless of whether or not it is observed by others) has changed over the years, and how this might influence our opinions of media use and its effects and may, in part, account for the dystopic view that seems to be dominating public discourse on the topic. 

One change: media use has become more public, and hence more visible. People watched a lot of TV before, teens used instant messenger a lot before, but they engaged in these activities mostly in their own homes. The ascendant variety of media use, mobile media use (primarily smartphones), is much easier to observe than TV use or AIM use on a home computer. Thus, we may think that there is a lot more media use going on than there was before, but this may be distorted by the fact that it is simply more easily observed. Evidence suggests that average screen time is increasing, but by the way people talk about digital media, you would think we spent very little time staring at screens before the smartphone, or that smartphones have doubled the amount of time people spend looking at screens (the real change in average screen time among Americans over the past 4 years is probably around 7%).

There are, of course, older media that are used in public: books, newspapers, and magazines. But there is an important difference between print media and smartphones: in the case of print media, it is easy for observers to know precisely what the print media user is reading while it is difficult for observers to tell what users are doing with mobile media. Observers cannot see the screens of smartphone or tablet users; even when observers physically can see the screens, there is an expectation that they do not look too closely at them. So, observers know that the other person is using media but they don’t know how they are using it: work email, liberal news, conservative news, nearby places to eat, connecting with family members on social media, bragging on social media, looking up how to build a bomb, how to build a raised-bed garden, etc.

What they are doing with media really matters. If they’re being social and supporting others while staring at the plastic rectangles in their hands, then this is very different than obsessing over how many people like what they've just posted on social media, and both these things can be done on the same website or application (e.g., Snapchat, Facebook, Reddit). There is such a broad range of activities in which a public media user could be engaged. My sense is that an anxiety arises simply because observers know so little about others that they share space with.

Then there's the question of what people would be doing if they weren’t using their phones. How do the particular activities in which they are engaged on their smartphones stack up to those other possibilities? If they weren't engaged in those media use activities, would they be talking to other strangers face-to-face? Would they be reading a magazine? Would they have spent time in deep, productive contemplation? Would they have stood there and dwelt on a mistake they made the day before? Would they have stayed home and watched TV? I ask these questions not in a rhetorical sense, to assert that the fear and resentment so many feel about media use is exaggerated. I raise them because I honestly don’t know, and that I believe that one cannot honestly say whether the fears about increased screen time and smart phones are justified or not without evidence that speaks to these questions. 

What about witnessing the media use not of strangers, but of someone more familiar to us: a friend, spouse, parent? Our observations of strangers are largely free of interpersonal influences; whether two people at the park talk to one another or ignore one another and stare at their smartphones doesn't directly affect our interpersonal relationships with them or anyone else. It's simply a snapshot of behavior in our society. When we witness the media use of someone with whom we have some sort of relationship, there is an emotional component to our judgment of their use. Commonly, we compare their media use to one particular alternative: having a good conversation with us.

This view ignores other alternatives. If they didn't have a smartphone or laptop, perhaps they would have elected to watch television, or would have elected to leave the room and call a friend on a landline phone in the other room, or would have read a book, newspaper, or magazine. Perhaps we would have had all of their attention instead of some of it, but perhaps we would have had none of it. We only see that they are not talking to us, which is something we wouldn't see and be reminded of if they were not in the room with us.

Compare the experience of sharing a room with someone you know while that person uses a smartphone to the experience of watching TV with someone you know. In the case of the TV-watching friend, we know what our friend is watching; we're watching it, too. In the case of the digital media user, we're likely to fear the worst when we can't see what the other person is doing on their smartphone or laptop, and the fear (of not really knowing this person and what they're up to) likely has a greater impact on us when it is a close friend, spouse, child, or parent. TV can spark conversation, but then again, so can smartphone use. During my casual observations of smartphone use at bars and coffee shops, I've noticed frequent "screen sharing" behavior in which phone use serves as the impetus for conversation rather than an alternative to it. I've also participated in such "phone-aided" conversations at home with my wife.

When we see other people using smartphones and laptops, we feel ignored. We often compare the situation to ideal alternatives rather than making the effort to determine what the likely alternatives might be. We don't think about what the person is doing with the media (often because the expectation of privacy prevents us from knowing this). When we see the elegant, charismatic performer transformed into a hunched-back zombie, we feel a visceral repulsion. This is what we do by default. We then seek out justification for these feelings in anecdotes, books, articles, documentaries, etc.

Making any sort of correct judgment about the impact of media technologies on society necessitates that we recognize the ways in which we respond emotionally to the sight of other people's media use. By the looks of the most popular opinions on smartphone and laptop use, many of us have yet to take that step.

The Truth, Online

Reading Jill Lepore's review of Michael Patrick Lynch's new book, The Internet of Us, reminded me to write something on the topic of truth. I haven't read Lynch's book yet, but even the sub-title ("Knowing more and understanding less in the age of big data") gave me that all-too-familiar twinge of jealousy, of feeling as though someone had written about an idea that had been gestating in my mind for years before I had the chance to write about it myself, of being scooped. So, during this brief lacuna between the time at which I learned of this book's existence and the time at which I actually read it, let me tell you what I think it should be about, given that title. That is: how is it possible that the Internet helps us to know more and to understand less? Or, to take Lepore's tack, what is the relationship between the Internet/Big Data and the truth/reality?

At this stage, I have only a semi-organized collection of ideas on the topic. I'll base each idea around a question.

To what extent has truth (or reality) become subjective in the age of the Internet/Big Data? 

I think we vastly overestimate the extent to which the Internet has fragmented our sense of truth and/or reality. And by "we," I mean most people who think about the Internet, not just scholars or experts. My sense is that it is a commonly held belief that the Internet allows people access to many versions of the truth, and also that groups of people subscribe to the versions that fit their worldviews. This assumption is at the core of the "filter bubble" argument and undergirds the assertion that the Internet is driving fragmentation of polarization of societies.

I contend that most people agree on the truth or reality of most things, but that we tend not to notice the things we agree on and instead focus on the things on which we do not agree. Imagine that we designed a quiz about 100 randomly selected facets of reality. We don't cherrypick controversial topics. It could be something as pedestrian as: "what color is they sky?" ; "if I drop an object, will it fall to the ground, fly into the sky, or hover in the air" ; "2 + 2 = ?" I'd imagine that people would provide very similar answers to almost all of these questions, regardless of how much time they spend on the Internet. Even when we do not explicitly state that we agree on something, we act as though we believe a certain thing that other people believe as well. We all behave as if we agree on the solidity of the ground on which we walk, the color of the lines on the roadways and what they mean, and thousands of other aspects of reality in everyday life.

The idea that reality or truth is becoming entirely subjective, fragmented, or polarized is likely the result of us becoming highly focused on the aspects on which we do not agree. That focus, in turn, is likely the result of us learning about the things on which we do not agree (that is, of us being exposed to people who perceive a handful of aspects of reality in a very different way than we perceive them) and of truth/reality relating to these handful of aspects genuinely becoming more fragmented. Certainly, it is alarming to think about what society would look like if we literally could not agree on anything, either explicitly or implicitly; so, there is understandable alarm about the trend toward subjectivity, regardless of how small and overestimated the trend may be.

So, I'm not saying that that truth/reality isn't becoming more fragmented; I'm only saying that part of it is becoming that way, and that we tend to ignore the parts that are not.

It's also worth considering the way in which the Internet has unified people in terms of what they believe truth/reality to be. If we look at societies around the globe, many don't agree on aspects of world history, how things work, etc. Some of those people gained access to the Internet and then began to believe in a reality that many others around the globe believe in: that certain things happened in the past, that certain things work in certain ways. Reality and truth were never unified to begin with. The Internet has likely fragmented some aspects of reality and the truth for some, but it has also likely unified other aspects for others.

Maybe I'm just being pedantic or nit-picky, but I think any conversation about the effects of the Internet on our ability to perceive a shared truth/reality should start with an explicit acknowledgment that when people say that society's notion of truth/reality is fragmented, they actually mean that a small (but important) corner of our notion of truth/reality is fragmented. Aside from considering the net effects of the Internet on reality (has it fragmented more than it unified?), we might also consider this question:

What types of things do we agree on?

Are there any defining characteristics of the aspects of truth/reality on which we don't agree? When I try to think of these things (things like abortion, gun rights, affirmative action, racism, economic philosophy, immigration policy, climate change, evolution, the existence of god), the word "controversial" comes to mind, but identifying this category of things on which we don't agree as "controversial" is tautological: they're controversial because we don't agree on them; the controversy exists because we can't agree.

So how about this rule of thumb: we tend to agree on simple facts more than we agree on complex ones. When I think of the heated political discourse in the United States at this time, I think about passionate disagreements about economic policy (what policy will result in the greatest benefit for all?), immigration (ditto), gun rights (do the benefits of allowing more people to carry guns [e.g., preventing tyrannical government subjugation, preventing other people with guns from killing more people] outweigh the drawbacks (e.g., increased likelihood of accidents; increased suicide rates], and abortion (at what point in the gestational process does human life begin?). These are not simple issues, though many talk about them as if the answers to the questions associated with each issue were self-evident.

I can think of a few reasons why truth/reality around these issues is fragmenting. One is, essentially, the filter bubble problem: the Internet gives us greater access to other people, arguments, facts, and data that can all be used by the motivated individual as evidence that they are on the right side of the truth. In my research methods class, I talk about how the Internet has supplied us with vast amounts of data and anecdotes, and that both are commonly misused to support erroneous claims. One of these days, I'll get around to putting that class lecture online, but the basic gist of it is that unless you approach evidence with skepticism, with the willingness to reach a conclusion that contradicts the one you set out to find, you're doing it wrong. Dan Brooks has a terrific blog post about how Twitter increases our access to "straw men." So, not only does the Internet provide us with access to seemingly objective evidence that we are right; it also provides an infinite supply of straw men with which to argue.

In these aforementioned cases in which we disagree about complex issues, we tend not to disagree about whether or not something actually happened, whether an anecdote is actually true or whether data is or is not fabricated. Most disagreements stem from the omission of relevant true information or the inclusion of irrelevant true information. We don't really attack arguments for these sins; we tend not to even notice them, and instead talk past each other, grasping at more and more anecdotes and data (of which there will be an endless supply) that support our views.

If it is the complex issues on which we cannot agree, then perhaps the trend toward disagreement is a function of the increasing complexity and interdependency of modern societies. Take the economy. Many voters will vote for an elected official based on whether or not they believe that the policies implemented by that official will produce a robust economy. But when you stop and think about how complex the current global economy is, it is baffling how anyone could be certain that his or her policies would result in particular outcomes. Similarly, it is difficult to know what the long-term outcomes of bank regulations might be, or military interventionalism (or lack thereof). Outcomes related to each issue involve the thoughts, feelings, and behaviors of billions of people, and while the situations we currently face and those we face in the future resemble situations we've faced in the past (or situations that economists, psychologists, or other "ists" could simulate), they differ in many others that are difficult to predict (that's simply the nature of outcomes that involve billions of people over long periods of time). And yet we act with such certainty when we debate such topics! Why is that? This leads to my last question:

Why can't we arrive at a shared truth about these few-but-important topics?

First, there is the problem of falsifiability. Claims relating to these topics typically involve an outcome that can be deferred endlessly. For example, one might believe that capitalism will result in an inevitable worker revolution. If the revolution hasn't occurred yet, that is not evidence that it will never occur; only evidence that it hasn't occurred yet. There's also the problem of isolating variables. Perhaps you believe that something will come to pass at a certain time and then it doesn't, and you ascribe the fact that it doesn't to a particular cause, but unless you've made some effort to isolate the variable, you can't rule out the possibility that the cause you identified actually had nothing to do with the outcome.

There are falsifiable ways of pursuing answers to questions relating to these topics. And despite all the hand-wringing about the fragmentation of truth/reality on these topics, there are also plenty of folks interested in the honest pursuit of these answers; answers that, despite the growing complexity of the object of study (i.e., human behavior on a mass scale), are getting a bit easier to find with the growing amounts of observations to which we have access via the Internet.

The other problem is the lack of incentive to arrive at the truth. Often times, we get immediate payoff for supporting a claim that isn't true, in the form of positive affect (e.g., righteous anger, in contrast to the feeling of existential doubt that often comes with admitting you're wrong) and staying on good terms with those around you (admitting you're wrong is often inseparable from admitting that your friends, or family, or the vast majority of your race or gender or nationality are wrong). So, there are powerful incentives (affective and social) to arrive at certain conclusions regardless of whether or not these are in line with truth/reality. In contrast, the incentives to be right about such things seem diffuse. We would benefit as a society and a species if we all right about everything, right?

I suppose some would argue that total agreement would be bad, that some diversity of opinions would be better. But we don't tolerate diversity of opinion on whether or not the law of gravity exists, or whether 2+2 = 4. Why would we tolerate it in the context of economic policy? Is it just because of how complex economies are, and that to think you have the right answer is folly? (I suppose that's a whole other blog entry right there, isn't it). But certainly, even if you believe that, you'd agree that some ideas about economies are closer to or further from the truth and reality of economies. So, perhaps what I'm saying is that if we lived in a society where "less right" ideas were jettisoned in favor of "more right" ideas, we would all benefit greatly, but that the benefits would only come if a large number of us acted on a shared notion of the truth and that the benefit would be spread out among many (hence, "diffuse").

But what if there were an immediate incentive to be right about these complex issues, something to counter the immediate affective and social payoffs of being stubborn and "truth agnostic?" I love the idea of prediction markets, which essentially attach a monetary incentive to predictions about, well, anything. You could make a claim about economic policy, immigration policy, terrorism policy, etc., and if you were wrong, you would lose money.

Imagine you're a sports fan who loves a particular team. You have a strong emotional and social incentive to bet on your team. But if your team keeps losing and you keep betting on your favorite team, you're going to keep losing money. If you had to participate in a betting market, you'd learn pretty quickly how to arrive at more accurate predictions. You would learn how to divide your "passionate fan" self from your betting self. And if you compare the aggregate predictions of passionate fans to the aggregate predictions of bettors, I'd imagine that the latter would be far more accurate. I would assume it would work more or less the same way with other kinds of predictions. People would still feel strongly about issues and still be surrounded by people who gave them a strong incentive to believe incomplete truths or distorted realities. But they would have an incentive to cultivate alternate selves who made claims more in tune with a shared reality.

Of course, not all issues lend themselves to being turned into bets (how would one bet on whether or not life begins after the first trimester?), but it still seems like, at least, a step in the right direction, and gives me hope for how we can understand the truth and our relationship to it in the Internet age, perhaps even better than we did before.

Looking Back on the Start of our Lives Online

I've been blogging for about 10 years as of last month. I started the blog during my first semester of graduate school at the University of Texas. Now, ten years later, I'm in my first semester as an Assistant Professor. I've used the blog as a way to catalog ideas related to my work and passion: understanding media use, in particular new/digital media use. I like to think that I've been able to refine my thinking on this topic through this blog. If nothing else, the blog serves as a record the evolution of my thinking. It allows me (or anyone else) to travel back in time and see how I thought.

While we're on the subject of travelling back in time (as a nostalgist, this is subject to which I obsessively return), I'd like to go back even further, about 20 years ago, to the time when I first started using the Internet. Recently, I was prompted by a question: "what was it like to use the Internet in the 90's". I took this to mean, "what did it feel like?" Here are some thoughts:

The big difference between the online experience then and the online experience now, one that many young people today wouldn't think about, is the way in which search engines changes things. In the mid-90's, you had to either hear about a specific website from a friend, a magazine, or TV (though no one in mainstream media really cared about the internet, so it was mostly through friends). Then you had to type the specific web address into the Netscape Navigator browser address bar. Good search engines (and the explosion of worthwhile websites in the late 90's) changed the online experience from hopping around a small series of content islands to something that feels like moving through one's everyday offline life. You went from hearing about a particular website (the way you would hear about a particular book or movie) to just thinking of something, anything, typing it into a search engine, and finding it.

Reflecting on the changes wrought by search engines made me think about a similar big change in media choice that affected what it felt like to use the medium: the remote control. Both search engines and remote controls came along at a time when the number of available options exploded (in websites, or in cable television channels). They made the explosion of options manageable. The feeling of the media use experience changed in both cases, from a consideration of several options (akin to being in a store or a library and making a selection) to moving through a landscape, observing things around you and reacting to them, and at the same time, conjuring or creating a world from thin air, thinking of something and having it appear in front of you.

We are different selves in those situations (this is an idea that I keep coming back to: the ways in which our environment brings out different selves). In the first, we are a chooser. But in the second situation, there are a few selves that could be brought out or summoned. In the second situation, we are potentially a react-er, but also a creator, an unrestricted curious, creative impulse. We are also, potentially, an unrestricted Id, acting on inner impulses for immediate gratification, reacting not to the outer landscape but to subtle shifts in our moods or thoughts.

One of my big questions: How do you foster curiosity and creativity and downplay reactivity and the impulse for immediate gratification? The answer, I think, lies in manipulating (perhaps a kinder word would be "customizing") the choice environment, and we've only begun to do this, and not in a systematic manner. And that is what I want to do with my research.