Early indications September 2020: YouTube and Drill Music

A month ago I had no idea what drill rap was. Then I read a review of a new book, Ballad of the Bullet, in The Economist. Thanks to the wonders of Covid librarianship, the school’s copy was shipped to me a few days later, and I then read a thoroughly engrossing and impressive piece of scholarship.

Eight years out of his UCLA PhD, Forrest Stuart is now a sociology professor at Stanford, but in the interim he taught at the University of Chicago and ran an after-school program aimed at helping community members cope with the violence of their surroundings. Once he was exposed to the rappers from the neighborhood who were trying to follow the path blazed by Chief Keef (Keith Cozart), Stuart embedded himself with them and saw firsthand the intersection of a sliver of opportunity amidst crushing poverty, social media popularity (driven by taunts of bravado), and street violence resulting from that bravado being challenged or usurped. The artifice of created personas, distributed via free online channels, fueled both multiple trappings of success (a new variant on sex, drugs, and rock and roll) and physical constraints on movement outside one’s turf.

Much as “reveal codes” taught a generation of people HTML 20+ years ago, so too was the YouTube/music playbook open for all to read. Cozart unleashed a fierce style of rapping, shaped by the brutality of his surroundings, that stood out from most other types. The videos reinforced the harshness of the sonics and were not the product of hundreds of thousands of dollars in production expenses. Authenticity and a Darwinian epistemology were paramount. As Stuart summarizes the movement, “If there is a dominant message running through virtually every drill song, video, and related content, it’s an appeal to superior authenticity: I really do these violent deeds. I really use these guns. I really sell these drugs. My rivals, however, do none of this.” (p. 6) Copying Cozart’s visual style, production techniques, distribution channels, and lyrical subject matter was straightforward, and Chicago became the home of a musical subgenre that has spread to London, Los Angeles, and elsewhere. As of 2016, 31 of 45 gangs in a six-square-block area had uploaded YouTube content. (p. viii)

Paradoxes abound. In contrast to the one Laptop Per Child school of thought, the teens Stuart observed were extremely adept at social media from a smartphone orientation; laptops for tasks such as video editing were hard to come by. Rather than learn conventional school subjects, the “drillers,” as Stuart calls them, were focused on social media. This focus took several forms. Primarily, one broadcast one’s persona via YouTube, Facebook, and Instagram. The fact that these were personas sometimes escaped police and prosecutors, who took social media posts literally, then used them as evidence of activity that may or may not have actually transpired. (Stuart notes the difference between black teens posing with firearms and white counterparts who were tolerated, celebrated, or applauded by police.) In addition, social media was also used as operational intelligence, predicting opposing gang members’ whereabouts, ideally unsuspecting and/or unaccompanied. Drive-by shootings could follow.

Second, for all the national fame (at different times in the book Stuart’s drillers travel to Indianapolis, Atlanta, and Los Angeles), being recognized even a block or two outside one’s home turf could be extremely dangerous. One consequence was to be “found wanting,” as one was forced on camera to renounce one’s gang superiority, walk back one’s prior claims (a certain kind of poser was known as a “computer gangster”), and commit other emasculations. 

Third, the benefits of fame tended to be more social than financial. Much as most blues musicians were never paid royalties by record labels, drillers often uploaded their videos to sites owned by videographers, producers, or other people more expert in managing Google’s revenue-sharing. Cash payouts could come when rappers were “featured” on another aspiring artist’s videos, but cash also was expended on said videographers and recording studios. In addition, other entities cashed in on the drillers, ranging from bloggers who highlighted social-media “beefs” that could in these quarters escalate to violence to Google and Facebook themselves. Instead, the benefits of local fame — “clout” in the nomenclature — could be as simple as getting respect from one’s family (one rapper had been kicked out of his mother’s house before finding fame and being let back in) or getting attention from females in the court of teen public opinion.

The book’s insights are many.  While there may be posturing that suggests drug dealing, for many teens climbing the hierarchy of the “corporate” gangs of the ‘80s is no longer an option: established dealers distance themselves from the social media frenzy and no longer stake out a newcomer to the operation with product and a market to prospect. The teens depicted in the book actually lost money in their brief experiment with dealing, through friends-and-family discounts, stolen stashes, and too many in-house samples of the product.

Rather than make money on drugs, the drillers quickly learn algorithmic scaffolding: unknown rappers can capitalize on better-known acts by posting “diss tracks” that use big viewership numbers to pull the newcomer along, albeit at real risk: you can only insult a national name so many times before retaliation comes. Elsewhere, the stereotype of the “digital divide” is tested, found wanting, and replaced by a more nuanced view of “digital disadvantage” among the urban poor. Micro-celebrity for these YouTubers is not of the same variety as that of travel “influencers” or fashion bloggers: they can’t quit if the rewards are insufficient or the blogger gets bored. This all-in pursuit of fame can be two-edged: as teens grow into adulthood and perhaps seek to leave gang life behind, erasing one’s social media presence, linked as it is to the gang, can be much more difficult than getting the tattoos removed.

There is much more to applaud. Stuart reflects carefully and usefully on the dangers of ethnography as voyeurism or self-aggrandizement. Ballad of the Bullet has much to teach about poverty and its potential remedies, about race and racism, about the atypical adoption (and consequences) of digital technologies. Most centrally, the highly consequential intersection of online fame with street-level mortality fuels new insights in the larger inquiry into online video’s many externalities. Forrest Stuart brings stand-up credibility, clear prose, and reflective insight to a corner of the Internet few adults will have encountered. His book broadened my perspective markedly, and I recommend it enthusiastically.

Early Indications August 2020: Book Review of Thomas Gryta and Ted Mann, Lights Out: Pride, Delusion, and the Fall of General Electric

As with so many aspects of economics and finance, an entity’s name often says little about what it actually does or contains. The Dow Jones Industrial average, a basket of (currently) 30 stocks, has never really been an accurate reflection of the U.S. manufacturing sector. Founded in 1896 by Charles Dow (co-founder of current-day Dow Jones), the original index was comprised of 12 companies, many of which represented what today might be called basic materials: cotton oil, sugar, tobacco, rubber, lead, and coal. The “Distilling & Cattle Feeding Co” is still with us as Jim Beam, now owned by the Japanese Suntory group. Laclede Gas still provides natural gas to communities in Missouri. Any pretext of only tracking companies that made things was quickly lost: AT&T and Western Union joined in 1916; Sears Roebuck and F. W. Woolworth were added in 1924. More industrially, General Electric was one of the original 12 companies on the Dow, dropped off two years later, and readded in 1899. 

GE’s long presence on the Dow belies the evolution of the company, which by 2000 was an advantageous blend of an investment bank and a heavy/advanced manufacturing conglomerate: in terms of naming accuracy, it was very “general” but not particularly “electric.” The business practices and assets of the factory-based side allowed the bank to borrow at the lowest possible interest rates at the same time that equity markets favorably valued the company more like a metal-bender than a bank. The double standard eventually disintegrated, and under CEO Jeff Immelt GE shed many of its financial services divisions in the midst of 370 divestitures; at the same time it acquired 380 companies. Bankers and lawyers were delighted — M&A fees ran an estimated $1.7 billion to fund the shuffle — while shareholders had less reason to cheer. This evolution eventually failed, and today GE faces fundamental reinvention. As it promises, Lights Out credibly tells the story of the fateful 20 years in which the company came to its moment of reckoning.

I had many questions that the book did not answer. For many years I taught whole sections of GE employees in my online supply chain masters classes at Penn State. Their devotion to Six Sigma/Lean Manufacturing was durable bordering on enthusiastic, but Lean is not usually a good tool for fostering radical innovation. I hope someday someone else is able to tell that story. Second, GE was a leader in adapting 3D printing to industrial production (not just prototyping) and while additive manufacturing wasn’t going to save the Titanic that was GE as of 2018, I wonder what is being salvaged from those pioneering efforts. The big question, which outsiders will never be able to answer, concerned the culture in which bad decisions went unchallenged by either the board or by middle managers with sufficient data to see pitfalls: the Alstom acquisition was built on shaky logic at the outset, and the EU’s pressure for concessions made GE leadership’s business case at closing completely fanciful.


Much of the book is devoted to the portrayal of CEO Immelt as global potentate, and rightly so. He flew with a spare business jet following him “just in case,” which cost shareholders many millions of dollars over his period in the job. Meetings with kings and presidents were part of the job; GE was one of those companies not only too big to fail but too big for political leaders to ignore. For all his skill in these settings, the job as Immelt defined it removed him still further from customers and their market realities.

Immelt made his name as a salesman, and the personality trait of not taking no for an answer (and the unshakable confidence a master closer must possess) led to multiple deals in which GE either overpaid or bought an asset for the wrong reasons: “synergies” that were so often promised rarely materialized on the income statement. More crucially, Immelt focused his attention far more on the share price than on his customers, and for all his desire to be valued like a tech company, GE appeared to have little of Apple’s human-centric design sense, Amazon’s customer-obsessiveness, or Google’s user-facing performance improvements. Knowing the complex financial structures of the business through the eyes of trusted lieutenants appeared to be far more important than step functions in the customer value proposition. Buying market share may work for a few quarters, but rarely did a Baker Hughes, an Alstom, or a Vivendi drive innovation and customer value.


One of Immelt’s highly visible missteps in his latter days was an apparently under-informed faith in the “industrial Internet.” This set of extremely expensive initiatives, designed more to goose the stock price than to deliver customer value, set out to establish GE as the Google of connected MRI machines, drilling platforms, and locomotives. It had all the signals of what a colleague in consulting once called “management by magazine,” the practice of a high-ranking executive reading some oversimplified account of computational magic and saying “make it so” in his or her company. Immelt showed no evidence of understanding cloud vs edge computing, networking and storage at massive scale, data curation, or the limits of data interoperability (standards and protocols). In and of themselves, these technical shortcomings shouldn’t be fatal: the Internet of Things is still in its early stages, and the challenge of instrumenting heavy machines and digesting the data they produce is non-trivial.

Immelt’s failing was more fundamental: he never seemed to have asked his business and technical experts for even back-of-the-envelope financial projections. Let’s assume sensors and analytics could deliver the promised 1% performance improvements — in jet engine fuel economy, in gas turbine reliability, in locomotive predictive maintenance accuracy. Who would pay for those sensors, that infrastructure, and the requisite brainpower? Companies that forked over multiple millions for a GE-made asset were (and are) not likely to pay for the privilege of letting GE siphon data from their assets only to sell it back to them in the form of more expensive service contracts: “here’s a way to run your generation facility longer between shutdowns. That’ll cost you $x million.” 


The story of GE’s embarrassing commercials featuring Owen the programmer who couldn’t lift his father’s sledgehammer and eschewed writing code for layering tropical fruits into photos of small furry animals turns out to be merely the tip of the Predix iceberg. Those commercials were intended for an ill-defined audience: 20-something data scientists weren’t turning down Facebook or Uber to work for GE, and the company’s buyers of capital equipment also did not react consistently favorably to the ads. Some contended that the campaign was intended for investors, who did not react as GE hoped, and the company’s retirees were largely furious at the tone as much as the content. Below the iceberg’s waterline, as it were, the combination of a naive (at best) business model with an insufficiently robust technical team meant that Predix was doubly doomed: making such a whiteboard vision work at scale still exceeds GE’s level of digital expertise years later, and even if the technology could have worked, there was never a realistic path to profitability in the market.

In the end, three aforementioned trends converged to bring down a mighty company: GE was dropped from the Dow in 2018, replaced by Walgreens Boots. First, the company relied more heavily on financial engineering (in the process, falling prey to Wall Street’s quarterly focus) than technical innovation. Second, GE lost focus on customer markets: Immelt bought and sold companies, not generators or drilling platforms. Finally, leadership got cute, trying to achieve with M&A what it could not with fundamental strategy and execution — while silencing voices of realism and dissent. Strategy, culture, and quality of execution all contributed to the fall of GE, which raises the question of lessons.


If we assume that companies age and decay faster than before — it’s hard to image another 120-year Dow tenure — companies like Microsoft, Google, and Apple are in mid-life. Many founders have disappeared: Apple lost its resurrected co-founder/messianic CEO almost 9 years ago, Google’s co-founders have retreated from operational responsibility, and Bill Gates is a hero of public health, not a monopolist-villain; Microsoft and Apple have both executed successful succession plans (the former after a 14-year mistake). The Economist recently profiled Google at mid-life (the jury is still out on its succession plan), and investors have to be very nervous about succession at Amazon. 


What can GE teach these companies? 1) Nothing can grow forever, and we see limits to scale: Dell peaked in 2006 and posted record net income in 2020 after six straight years of losses. IBM revenue peaked in 2011, arguably after its industry influence did. 2) Losing sight of customers and innovating to solve real issues can be fatal: Immelt and Steve Ballmer at Microsoft shared several characteristics, including being sales executives. 3) Managing to the share price is a real temptation that Jeff Bezos and Tim Cook (for very different reasons) have avoided. 4) Most important, you have to make the right technology bets and have the engineers who can make them work. GE had no signature customer-facing innovation for years, certainly nothing on the scale of Amazon’s cloud or Alexa platforms, Apple’s pivot to iPhone-linked services, or Google’s AI-powered operations in multiple markets. Call it revenge of the nerds, but the best CFO in the world can’t compensate for a shortfall of well-deployed and well-managed technical talent. Google has both a top-drawer CFO and terrific technical talent, but there are strains in the relationship between the two; Facebook too has cultural issues between programmers and management. It may turn out that keeping your engineers happy and well focused is the mark of a healthy company in the mid-21st century.

Early Indications June 2020: So many questions



I am both academically and temperamentally inclined to analyze the unintended consequences of technology innovation. That inclination can lead to some surprising juxtapositions. Right now, for example, I’m thinking that penicillin is part of the reason the current pandemic is so weird. To explain: as of 1930, with the 1918-19 influenza epidemic still fresh in memory, pretty much everybody had lived through severe illness outbreaks. Tuberculosis, polio, typhoid, malaria, and other diseases were part of the normal landscape. After DDT, antibiotics, vaccines, improved nutrition, better public infrastructure (especially water supplies), and indoor plumbing, the late 20th century saw many of these diseases recede from mass consciousness. As a result, we in 2020 lack mental models for processing what global patterns of infection look like. Accordingly, Covid-19 is fueling many (but certainly not all) of the questions we are confronting at this juncture. 


Like everyone else, I have never experienced a pandemic. While many questions (including “what do I wear?”) have sort of been answered (athleisure), the cascade of unknowns is overwhelming. Business and civic officials are faced with a huge, complex tangle of issues around which they must plan. We will have more to say about planning under uncertainty, but for now, the U.S. and most of the world confront an unprecedented (in our lifetime) web of questions.


I. Covid-19


Thinking back just 4 months is an exercise in cognitive dissonance, returning to a time when air flights, concerts and sporting events, and bustling restaurants were unremarkable. When large numbers of people can gather indoors again, it won’t be a simple reset. How different populations in different places move on will be a legacy of the pandemic, with many consequences both major and minor. For now, there's so much we don't know.


-Basic statistics
How many people have been infected or otherwise possess immunity? Of those infected, how many became symptomatic? How many people have a) directly and b) indirectly died because of Covid-19? How have the ratios of these numbers changed in the past 6 months? The one number we do seem to have — how many people have tested positive? — doesn’t really tell us much.


-Basic science
How exactly is the virus transmitted? How long will the Covid-19 virus remain stable (will there be a Covid-20 or 21 variant?)? How long does immunity remain viable? Can the virus’s traits that kill people be addressed by treatment? What if any long-term impacts will people develop in a year or five? That is, new research suggests that the virus can involve multiple body systems beyond the lungs including pancreas, brain, gut, heart, and immune system. Might a 20-year-old infected in 2020 develop debilitating lung scarring at 25, or age of childbearing, or at menopause? Might we see millions of cases of cardiac and/or cognitive damage at atypically young ages of onset? Assuming a billion people are eventually infected, and a quarter require long-term care, the costs in both money and lost human potential could be staggering. Or they might not be much more than a blip.



-Vaccination
Can a safe, reliable vaccine be developed? If so, how many people will consent to immunization, and how quickly? Most people have forgotten the 1976 flu vaccine program, which occurred during a presidential re-election landscape (Gerald Ford) and was rushed, largely unnecessary, and heavy-handedly promoted. The current public faith in the vaccine establishment is much less robust than it was 44 years ago, in part because of social media, and the understandable urgency to deploy a vaccine could lead to mistakes that a) harm people and b) drop credibility further.


-Symbolism
Mask-wearing has become politicized in ways few people could have predicted. Governors still hold considerable authority (withdrawing liquor licenses or certificates of occupancy for large venues), but the simplest tool has been taken out of play in many areas. What other responses to the virus might lead to shootings, fistfights, and other conflict?


-Economics
Travel and tourism along with hospitality have suffered substantially since March, and restaurants in particular look especially vulnerable. How many establishments can turn a profit at 1/3 or 1/2 seating capacity (after being completely out of business for a time)? Additionally, with conferences, trade shows, and large sporting events off the calendar for many more months, foot traffic will drop still further. Schools and colleges are other major economic actors that rely on large gatherings in indoor venues, and educators are becoming increasingly vocal in their refusal to return to classrooms under current plans (Fairfax, VA is an example). More than 30 football players at both LSU and Clemson have tested positive so far: even without fans in the stands, can those numbers drop to and remain at safe levels for close, hard-breathing contact for 3 hours at a shot? If not, both amateur and professional leagues could see multi-billion-dollar losses.


-The social contract
Thus far, vulnerable populations — the aged and low-wage communities of color — have suffered disproportionate fatalities in many countries. For a time, this appeared to be a policy calculus in some places. With the coming of fall, a bitter U.S. presidential election, and a projected resurgence of both Covid and influenza viruses, will those populations continue to be harder hit? Or might more affluent communities see dramatic and widespread effects, perhaps triggering tighter lockdowns than were implemented to safeguard more marginal groups? 



-Gatherings
Which venues will _stay_ open first? Which venues will people return to and which will see drops in participation? Churches, offices, bars, arenas, and trade shows will likely resume speed on different trajectories. The quick reopenings that are being followed by panicked closings (see: beaches, Florida) may fuel a more cautious ultimate return in some places than we saw in countries like New Zealand, where the governmental response was more coherent.


II. Black Lives Matter


Coincident with the pandemic is a broad-based movement to reverse centuries of institutional racism, beginning with more accountability for police officers who kill and abuse unarmed citizens without commensurate consequences. In addition to the public safety discussion, education, hiring and promotion practices, and cultural representations of people of color are suddenly front-burner issues in many places.


-What will police reform look like?
It’s easy to point to the abuses, but reversing them is complex. Different geographic units count things (or don’t count things) in different, non-standardized units: a drop in arrests could result from either bad policing or good policing. Prosecution of police officers depends on testimony from other officers, in trials initiated by prosecutors dependent on police cooperation in their everyday duties. Absent smartphone video, most policing crimes are neither reported nor prosecuted. Already police walkouts are occurring in response to even minor action by mayors. Personal safety is an emotional topic and police unions appeal to it at every opportunity.


-What constituency will drive change?
Speaking of police unions, political progressives are in a bind as they both march for police reform (or “defunding,” a word with many meanings) and seek to bolster labor union membership and bargaining power. Ethnic minorities, by definition, are minority populations even if they may be a majority in a precinct or locality. Suburban whites have marched and told pollsters they support change, but how deep or long-lived will that support be? How much management attention will be devoted to fixing policing in an economic recession in a pandemic in a period of high emotional anxiety and uncertainty? Put more bluntly, will fixing police brutality get a mayor re-elected if she doesn’t create jobs, fix potholed infrastructure, or maintain the aforementioned personal safety?


-How long will change take?
Universities pledge to hire and tenure more people of color: many groups are underrepresented in the professoriate and are rightfully speaking out. Businesses pledge to increase minority board seats and C-level appointments. Many people and groups seek to support Black-owned businesses. None of these commitments can be realized overnight. Between 2011 and 2017 the top 20 U.S. economics programs graduated a total of 15 Black PhDs. That’s collectively: in other words, about a tenth of a PhD per year per school. Filling the talent funnel will take decades, beginning in pre-K programs like Head Start. How can early gains be realized at the same time that structural reforms will necessarily take a long time to kick in?


-Where is the political will?
A divided U.S. congress has already claimed one effort to begin to address abuses in policing. State budgets are being crushed between increased Covid-related costs and decreased tax revenues. All politics may be local in the Tip O’Neill sense, but programs to equip police forces with military armament originate far away from city streets. Following the money reveals considerable cash devoted to the status quo. What coalition can change that?



-Where are the invisibilities?

There are many Americas, and residents of one can be oblivious to the others. I have only seen two or three Indian reservations that I know of (casinos notwithstanding) and that's probably by political design. Aggressive inequities in policing in Minneapolis are long-running, yet the Twin Cities routinely score well on quality of life indexes like this one: https://realestate.usnews.com/places/rankings/best-places-to-live. Ralph Ellison's _Invisible Man_ turns 70 years old in 2022, its relevance having outlived the war on poverty; Montgomery, Selma, and Memphis; the Voting Rights Act; Malcolm X; affirmative action; and so many other American beginnings that have yet to realize the fruition of true human inclusion.  

III. Macro-level dynamics


Even before the virus rearranged everyone’s lives in March, high-level social and economic winds were shifting. With new forces such as telework and telehealth suddenly accelerated by the virus response, life as we knew it in 2019 is likely gone forever in many regards. Despite lots of people talking about getting “back to normal,” our future non-pandemic life is going to require some adjustments.


-International trade
The trend toward globalization of the 1990-2019 variety was already slowing, and post-Covid-19, we will see new developments. China has become a true super-power and future negotiations will reflect that reality. Critical items like facemarks are too important to be manufactured only in plants far away from points of urgent need. A growing global middle class is loading the planet with demand for animal protein, motor vehicles, and air transportation, and every country will have to re-evaluate its role in that load. Factories can no longer be as easily relocated for convenience of low wages and lighter regulatory burdens.


-Technologies of fabrication and motion
Micro-manufacturing, micromobility, and advanced materials will transform transportation and manufacturing. Bicycles (which are selling fast these days) and pedestrians will play a bigger part in formerly car-centric urban planning. This shift in transit means more bike and light-rail factories and eventually fewer car-makers. How fast and how far air travel rebounds is another major uncertainty.


-Real estate
With the link of work and place broken, for good at some firms, real estate will be shaken up at all levels. Many malls, already an endangered species in the past few years, are going to fail sooner than they would have absent the pandemic. Office space will be scaled back in favor of telecommuting and virtual teams. People can buy houses where they want to live, to a greater extent, than they could when physical work presence was the rule. Such familiar practices as commutes, business travel, and industry gatherings will be redefined rather than simply resumed.


-Skills mismatches
Despite lots of people making creative pivots (corporate magicians and other entertainers doing Zoom sessions), the pandemic has heightened the realization that the current skills base both in corporations and coming out of universities doesn't align with what institutions (businesses, non-profits, governments) will need in 2025 or 2030. As Benedict Evans points out, internet telephony was not invented by Skype, nor could Skype dominate the market: many apps now have voice embedded. Might Zoom go the same way, breaking down an ease-of-use barrier only to see video embedded in social, learning, customer service, and other scenarios? Will resumes of the future embed the technology, essentially encapsulating the interview in the application document? The same questions can be asked of new manufacturing, advertising, retail, social service, and recreational-access technologies. Who will staff the organizations built on the legacy of the Covid-19 quarantine?


IV. How does one cope?


The general sense of anxiety is widely reported: major uncertainties cloud one’s health and safety, economic well being, kin and friendship networks, and future prospects for one’s offspring. The huge academic literature devoted to decisions under uncertainty isn’t much help. Much of it is written to support neural network and other machine learning research. Other bodies of work (including the Nobel-winning contributions of Tversky and Kahneman) show how humans revert to known patterns in the use of heuristics rather than relentless examination of the evidence. Further, many decision models are built on binary outcomes: the election will be won by a Democrat or a Republican, the student will attend college or not attend college, tomorrow it will rain or not rain. What we are faced with now is far from such simplicity: economic recession and/or recovery and policing that no longer commits the crimes of the current institution are non-binary futures. Modeling our current future is an exercise in murkiness.


Let me end with a prediction based on hope more than evidence. With travel curtailed, with commuting redefined, and with people taking a bigger role in urban transport (vis a vis automobiles), perhaps we will see a resurgence of physical community, of neighbors taking action alongside neighbors, putting aside the “virtual” social networks that have proven to be so toxic to the republic and to the body politic. If we take Tip O’Neill at his word then perhaps a corollary is that all localism can generate political change.

Early indications July 2020: Our digital twins?

Seeing the major US tech CEOs testifying before Congress earlier this week is a useful prompt to consider just what it is those companies sell to become so powerful. Amazon sells household goods, information goods, groceries, computing capability, and now eyeballs: 2019’s $14 billion in ad revenue was a 40% jump on the prior year. (For perspective, that’s more than the company made on cloud services as recently as 2016.) Apple sells high-margin hardware, and increasingly services: at about $50 billion a year (annualized), the App Store, iTunes, cloud storage, and the like outperformed most of the company’s hardware lines, but not the iPhone. Google and Facebook, however, are less diversified: they each sell some version of us.

What we will consider this month is the degree to which the digital representations of us that are modeled and manipulated by the ad giants mimic a notion with its origins in heavy industry: the digital twin. Briefly, a GE, Boeing, or Caterpillar can aspire to accumulate and crunch sensor data from thousands or millions of Internet-connected Things such as jet engines, MRI machines, airframes, or excavators. Identification of safety risks, predictive maintenance optimizations, and other business processes is the grail in this world: it’s far better for BNSF to have a digital locomotive fail in a simulation than the physical one 500 miles from a breakdown crane. As with self-driving cars, all data-powered products (think of Tesla’s over-the-air software upgrades) can theoretically be as capable as the most capable unit. As of now, the industrial digital twin is closer to whiteboard aspiration (see this new book about GE’s failures) than to profitable reality.

It’s pretty obvious after spending any time on a modern digital platform that its algorithms are easily fooled. Run a few searches for birthday presents for someone, and your ad feed quickly resembles the demographic of your giftee. Now that I have a physician in the household accessing Epic and other clinical systems, I get “overspray” in the form of ads for prescribers of IUDs by virtue of sharing a network, apparently. The reference librarian knows I’m writing a research paper on government policy regarding Puerto Rico whereas Google responds as though I want to vacation there.

At one level this slippage is reassuring: I used to get ads for industrial ropes and slings in my Gmail header, not to mention ads from malpractice lawyers representing patients with complications from the implantation of transvaginal mesh. At the same time, the uncanniness of ads has led to widespread suspicion that open microphones are capturing spoken conversation. There’s also the head-fake to consider: Target used to send coupons that too closely resembled a person’s interests or shopping list, and customers were creeped out. Target’s solution, if I recall correctly, was to add “noise” coupons to calm suspicious consumers: there’s nothing like a lawn mower ad to distract from how much the store knows about your health and beauty purchasing habits.

At the same time that we are (mis-)represented by behavioral data collected both on- and off-line, in unfathomable quantities, that can vary widely from our “real” selves, there are data representations of us of much higher fidelity. None of these are _currently_ aimed at trying to get me to do something, though as we will see, the lure of ad revenue extends farther and farther, to include ISPs for example. Verizon/AT&T have an extremely accurate map of my daily movement, provided my phone is within a few feet of my person most of the time. Smart TVs and cable boxes track viewing habits, with the data shared in sometimes-objectionable ways. (Devices from multiple manufacturers share behavioral data with Google, Facebook, and Netflix, for example, and opting out is predictably difficult.) Personal fitness trackers and exercise trainers are another source of high-fidelity data that could someday contribute to a “digital twin.”

Google and Facebook get paid when we click on ads. Ideally, Aetna should want me to live a long and healthy life with few expensive conditions/episodes and I presumably agree. How much will these two trajectories — digital twin as behavioral experiment vs digital twin as predictive maintenance — diverge vs converge?

This is pure speculation, but I think the player to watch is the richest CEO from the congressional hearing the other day. Amazon has 1) a vast store of behavioral, social network (in the form of our address books and gifting history), and purchase data, 2) unsurpassed computational power and algorithmic talent, 3) designs on medical markets, as evidenced by its PillPack acquisition, and 4) strong motivation to lower health care costs for its enormous — soon to approach one million — workforce. (I missed it, but Harvard surgeon and New Yorker author Atul Gawande left the CEO post at the Amazon/Berkshire/JPMorgan Haven Healthcare startup back in May.) Amazon warehouse workers already wear wristbands to track movement and allegedly productivity. If there’s a digital twin of an employee already built, the e-commerce behemoth is as likely as anyone else to have built it. 

Where might we go from here? Behavioral nudges — to lose 5 pounds, to get up from the desk and stretch, to eat more vegetables — would seem to be a perfect marriage of the two trajectories. Back in the days of e-commerce, Pets.com discovered a powerful predictive question: if the website visitor bought his or her animal a present on its last birthday, they were substantially more likely to make a purchase than a site visitor without that behavior. Where else can big data expose similar minimally invasive but predictively powerful indicators of long-term well-being? If I were inventing a “dream” college graduate right now, she’d have some combination of algorithmic aptitude, behavioral economics, and engineering training to understand big data, human motivation/reward, and systems thinking. 

Bearing in mind the fact that the man behind Facebook’s explosive growth between 2007 and 2011 won’t let his own children near the “short-term, dopamine-driven feedback loops that . . . are destroying how society works,” how might the future be better? The first thought is algorithmic transparency, a phrase that has yet to be operationally defined, as Microsoft’s danah boyd has shown: few of us could read the algorithm, and the algorithm is an abstraction without user data, raising privacy hurdles. Second, there has to be a working definition of ownership: at some point, a person’s data footprint should be under his or her influence rather than being remote and inaccessible. Realistically, this would mean FTC- or FDA-like regulation. Third, we need better sensors, better sensor protocols (including for privacy), and better sensor-data analytics: if AM General can’t predict when the Humvee transmission will fail in Afghanistan vs in Alabama, Mass General is still a long way from identifying when I will have a stroke. 

Last, I would be in favor of intensifying training in critical thinking. The echo chambers so powerfully created and manipulated by Facebook (among others, obviously) would gain less traction if more people sniffed out hoaxes and self-serving propaganda. Scientific literacy appears to be in retreat, in part, it appears, because of those “short-term, dopamine-driven feedback loops”: people, it turns out, are incredibly easy (and profitable) to game.

How can we as parents, as educators, as citizens, as humans demand — and model — better? It sounds paradoxical, but better critical thinking and digital literacy skills will help us build new kinds of organizations — of learning, of governance, of news/media — to replace today’s so visibly broken ones. Restoring institutional credibility and cognitive authority (in short: trust) in our institutions, nurturing humanistic leaders who grasp the realities of today’s vast machines of data collection and behavioral manipulation, will be a long road, but one I believe is worth hiking, one careful step at a time.

Early Indications May 2020: Platforms and Truth

As I write the president has recently signed an executive order that desires to change the status of Internet platforms’ responsibility for the content their members post. The regulation in question, which originated in the Communications Decency Act of 1996, has a long and fascinating history. Here’s the text in case you’re interested.

In its early years of owning YouTube, Google invoked the “safe harbor” provision of the CDA to exempt itself from responsibility for much of the content that YouTube’s users uploaded. Even though the CDA was ruled unconstitutional by the U.S. Supreme Court, the “safe harbor” concept remained in force, eventually in section 230 of the United States Code, which is the legal underpinning of the Federal Communications Commission. Section 230 does two things. First, it protects providers of Internet services from liability for the speech exercised by users of that infrastructure. Second, when those providers do choose to police some speech or behavior, it does not imply that they must police all behavior.

Tarleton Gillespie of Microsoft Research points out a crucial distinction: section 230 was meant to apply to Internet Service Providers like AOL or Comcast, but was quickly invoked by social media companies a few years later. Because Facebook and YouTube are exempted from responsibility for what their users post, except in a few extreme cases of child endangerment and terrorism, these companies have been slow to regulate other troubling behavior. Because the law in the U.S., where the companies are headquartered, is so favorable, those companies act to moderate content primarily for economic reasons rather than legal ones. Google has repeatedly failed to pay fines levied on it by the EU. For its part, eBay first tried to block sales of Nazi-related items in only France and Germany but, finding that nearly impossible, pulled such items from the site entirely (except for postage stamps and the like). The point here is that U.S. economic logic is dictating what billions of non-U.S. citizens see and don’t see.

Note that YouTube and its kin in the U.S. are (lightly) regulated by the laws related to the phone companies. YouTube is of course heavily reliant on telecommunications, but it is also a near neighbor to the movie industry (governed largely not by federal law but by self-regulation: movie ratings derive from the Motion Picture Association of America, a trade group) and in some ways to newspapers (in the U.S., under the umbrella of the First Amendment related to freedom of the press, and thus regulated by court cases). Further, Google, as a major actor in the advertising ecosystem, is subject to oversight by the Federal Trade Commission. Predictably, any entity that spans so many jurisdictions – in only one country representing a minority of its total traffic – can often escape close scrutiny by claiming exemption from any given mandate.

For the platforms, section 230 is a great gift. Facebook et al can profit from content they neither produce nor must police. Inaccuracy, whether inadvertent or aggressive and programmatic, is rampant, and profitable. Digital literacy is troublingly low – especially when sites that could be used for fact-checking, namely Google, surface results that have been cleverly promoted by peddlers of falsehoods. Anti-Semitism, anti-vaccination falsehoods, misogyny, and racial stereotypes only begin the list of search areas that have been gamed. 

The current debate will be important to watch. Since March, YouTube has been much more activist, both in removing false content in relation to the coronavirus and in generating positive, accurate videos under its own branding, using the #WithMe hashtag. At Facebook, Mark Zuckerberg allows political ads and commentary to say almost anything (official company policy notwithstanding), and internal voices concerned about the site’s practice of ideological polarization were silenced. Twitter, as we saw this week, has a long history — of allowing harassment and verifiably false statements to stand -- that it will have a hard time walking back. The Biden campaign, for its part, is on record as opposing section 230, but in the direction of requiring platforms to do more policing of content, not less, as the Trump position argues.

This state of affairs, as lamentable as it is, stands in stark contrast to the technological optimism of the computing pioneers responsible for the conceptual and technical foundations upon which the Web, and later its platforms, were built. Stewart Brand migrated from the Whole Earth Catalog’s neo-homesteading ethos at the tail end of the 1960s to early online communities and the tellingly named Electronic Frontier Foundation. Tim Berners-Lee and his co-authors in 1992 articulated the ideal of the World Wide Web:

You would have at your fingertips all you need to know about electronic publishing, high-energy physics, or for that matter, Asian culture. If you are reading this article on paper, you can only dream, but read on. Since Vannevar Bush’s article (1945) men have dreamed of extending their intelligence by making their collective knowledge available to each individual by using machines.

Only six years after Berners-Lee, however, James Katz of Rutgers (formerly at Bellcore, the Bell operating companies’ R&D shop) astutely saw the potential for the Web to pollute that stream of knowledge rather than nourish it:

The Internet and the Web allow for the quick dissemination of information, both false and true; unlike newspapers and other media outlets, there are often no quality control mechanisms on Web sites that would permit users to know what information is generally recognized fact and what is spurious.  

Katz basically called out Internet-powered fake news 22 years ago.

The rapid evolution from Berners-Lee’s extreme optimism to the many and profound downsides of ubiquitous connectivity – mental and physical health concerns, the monetization of private life via unmonitored behavioral experimentation, the hacking of democratic institutions, trolls and shitposting, swatting, aggressively nasty disregard for the views of women and ethic populations --  is a story for another time. The dilemma of a post-fact society cannot be probed here, but it is real.

At the same time, this is not for a moment to suggest the problems of accuracy in and abuses of online platforms are easy to address. Twitter’s vice president of trust and safety Del Harvey used simple statistics to drive home the scale of the moderation issue in a TED talk in 2014. “Given the scale Twitter is at, a one-in-a million chance happens 500 times a day,” he stated. That changes operating assumptions. “For us, edge cases, those rare situations that are unlikely to occur, are more like norms.” If you assume 99.999% of tweets pose no threat whatsoever, “that tiny percentage of tweets remaining works out to roughly 150,000 per month. The sheer scale of what we’re dealing with makes for a challenge.” Bear in mind that Harvey was speaking in 2014, when YouTube uploads were probably half of 2019 levels, and that YouTube sees three times the monthly active users Twitter has, and the scale of the moderation problem — that historically does NOT include fact-checking — gets tangibly staggering. 

This moderation problem is made harder yet by the platforms’ need to maintain the illusion of civility and neighborliness. Few platforms publicize their moderation teams; in 2013 an NPR reporter was denied access to moderators at both Google and Microsoft, though a spokeswoman at the latter said moderation was “a yucky job.” Much of the work is outsourced. One moderator told a reporter in the fall of 2019 he was paid $18.50 an hour (about $37,000 a year) to watch “VE” – violent extremism, primarily in Arabic – videos all day as an employee of Accenture, the tech services firm Google contracts with for some of its moderation. In October 2019 Google reported it had removed 160,000 pieces of violent extremism material from various of the company’s properties. That’s about 450 per day, every day.

Removing or changing the section 230 “safe harbor” concept could force the big U.S. platforms to alter their business models, YouTube potentially less radically than Facebook. The concept is also well established after nearly 25 years of court decisions, so the status of case law relative to executive order will need to be decided. In any event, a law intended to protect Internet Service Providers that evolved into the bedrock on which large-scale digital platform companies were built has suddenly and loudly been called into question.

Early Indications April 2020: Where comes next?

Between the coming of spring, a few epidemiology curves trending downward, and some promising medical news, it’s beginning to be possible to think about life after the coronavirus lockdown. My focus here will be on how place and space might be affected by the quarantine experiences.

Commercial space, political space, social space, and personal space are all likely to be rethought, in some cases temporarily and in others permanently. Shopping malls, already in trouble as a sector in the past few years, look ripe for reinvention or continued shutdowns. Telecommuting will be fascinating to watch relative to office real estate. If people can do all of their job tasks working from home during the lockdown, the old arguments against remote work will be hard to resurrect after it’s over. (I’m not saying co-location does not confer benefits: if anything, we will probably appreciate them more fully once we return to the office.) Look for the average number of square feet of office space per worker to continue its drop. Could a better-run WeWork-like entity find a market in the new normal of office space?

Just as there are important differences between moving a residential college course into online mode on short notice and ground-up redesign for the virtual medium, so too will work practices have to evolve as their locus changes. Here’s one example: hospitals are rushing to implement telemedicine and millions of patient visits have been successfully conducted. The workflow for the healthcare providers, however, is kludgey: the videoconference network, the hospital’s billing and record-keeping software, regulatory compliance software from the state (in the case of scheduled pharmaceuticals for instance), and the electronic signature all come from different vendors so the doctor or nurse becomes an ad hoc systems integrator with no additional time allotted in the daily schedule for the extra effort and frustration. 

Moving from a physical office visit to a virtual one includes updated workflows, additional infrastructure — both technical and cultural/organizational — and potentially new models of care: outside specialists can be patched into the video call, and patients’ home environments can be assessed in ways they cannot in a clinic. The location, size, and functions of clinics, showrooms, cubicle farms, and call centers can all be rethought given the creativity and will to do so. One quick win: hiring people with physical disabilities should become easier without the need for special transport or workplace modifications if the employee works from home, which can be anywhere with Internet connectivity, not just within reasonable drive time.

One fascinating aspect of the rush to online instruction is the cleverness and speed of students who hack the process. In China, students bombarded their learning package with 1-star reviews in the hopes the Apple app store would take it down and they wouldn’t have schoolwork. Plenty of students are learning about computers by reading the browser code for their quizzes: “if answer = 40 then points = 10” is pretty easy to figure out. Even some Zoombombers started out as high school kids putting 2 and 2 together (their own experience with organizing meetups) with a few Google searches for dial-in codes. Rethinking the workplace means rethinking security.

Another level of space is administrative jurisdiction. The economic shutdown was intended to “flatten the curve” of ICU admissions to prevent the kind of overload to the medical system that New York City is confronting as I write. For unknown reasons, some places are getting hit much harder than others: Lombardy vs Rome, New Orleans vs Tampa, Detroit vs Denver. Part of this pattern could be due to innate immunity or silent exposure that confers immunity: one survey of asymptomatic people in Iceland suggests 50% have the virus with no measurable signals. Obviously Iceland is far from representative of anything, but one piece of an economic re-start will have to be much wider testing to detect levels of potential community spread (and eventually community safety). That testing might be connected to contact tracing efforts, which could improve safety at the cost of privacy. In whom will people be confident with that trade-off? Banks, post offices, and insurance companies obviously market and sell trust, but are any of these good candidates for holding sensitive medical information at such large scale? Trust in tracing will be a major challenge: a Washington Post poll this week found few people excited about tech companies performing this function, and only about 40% of the sample was both technically capable and willing to trust _any_ entity.

The regional governors’ groups formed in response to the pandemic might wither away after the crisis, or maybe they will persist with new kinds of charges: water use, immigration, voting, education, and transportation might be candidates for regionalized response. For the time being, getting a better handle on the reasons for the dramatic geographic disparities in sickness and health will be imperative to restarting the global economy. 

Continuing on the theme of jurisdiction, how will public health agencies be situated going forward? Where do they operate? How are they funded? The WHO, CDC, and many state health departments have failed their charge of late; might there be appetite for new models of monitoring and response? Part of a return to normalcy will be a vaccine, and the Gates Foundation’s efforts to accelerate this process are obviously welcome and well-placed. Even so, getting tens of millions of doses to those who need protection most will be a massive effort. When vaccines become available, who gets them first? Best guesses have those vaccines ready in 12 to 18 months: in the interim, we need to build the social infrastructure of allocation and administration. What agencies will take the lead, and why? As with ventilators, we will need to pay attention to how scarce resources are allocated. As in many biomedical scenarios (blood and organ donation foremost), markets are a suboptimal tool for making these decisions.

The reinvention and redefinition of social space will be a critical aspect of the recovery. Because college football is a massive economic engine that supports essentially all of college athletics (except for Duke and Marquette basketball and a few other outliers), it has been in the national spotlight: everyone from hot dog vendors to sports bars to Disney (parent of ESPN) is suffering right now. College athletics could be permanently reshaped by this virus. Absent a vaccine, which cannot possibly be discovered and deployed in 4 months, how can colleges and universities allow tens of thousands of ideally screaming fans to stand inches apart? How many $5 million-a-year head football coaches will collect paychecks if no games are played? Will Covid-19 mutate to Covid-20 this fall and if so, will immunity to the former carry over? As employees, pro football players have rights and responsibilities college players — “scholar-athletes” as the euphemism has it — do not. The NCAA and NFL are unlikely to walk in lockstep as each copes with life during a prolonged pandemic.

Other social spaces will evolve as well. Yoked as they often are to malls, many movie theaters do not appear to have a robust future. State fairs, rodeos, religious worship, and concerts will be unrecognizable for a time. Orchestras in the US do not enjoy the level of community or financial support their counterparts in Europe see, so will some weaker organizations be forced to dissolve? French headlines predict many of the country’s art galleries will close permanently after the lockdown. Museums and other non-profits the world over will suffer possibly catastrophic economic losses and/or implement new admissions practices that enforce social distancing. What about parks and beaches? In densely populated areas especially, might the pandemic drive innovative urban planning to create new parklands, potentially reclaimed from roads closed to auto traffic in favor or pedestrians or bicycles, as in many European efforts?

Finally, the pandemic will forever change personal space. Breaking up via teleconference is now known as Zumping, I’m told. Watch parties virtually connect responsibly isolated friends or dating partners. Activity across various Facebook properties is surging, as is Netflix traffic. I saw a virtual doctoral dissertation defense and millions of students will experience graduation from a screen. Birthday parties have become truly creative, from drive-by honk-a-thons to surprise video greetings from celebrities. What is called “social distancing” is really a misnomer: we need our networks more than ever, but the imperative is to maintain _physical_ distance at the same time we struggle to remain socially close to the people who matter.

Video conferencing is incredibly different from what AT&T envisioned in the Picturephone almost 60 years ago. Multi-party meetings, shared screens, fake backdrops, and side-channel text are all important features. But the privacy implications of Zoom/Webex/Teams/Google Meet need to be explored. Here’s a thought-provoking essay. Leave aside for a moment the question of what data and/or metadata the conferencing provider is collecting. Zoom is terrifically intimate and we see into the home lives of co-workers, interviewees, students, and other people around whom norms traditionally created physical distance and structure. Now, there are dogs or babies or personal mementos to mark that 2-dimensional screen as theirs, but now also mine. School systems are wrestling with this privacy issue already: I as a parent would be extremely uncomfortable having random teachers see the bedroom of my child, but that may be the only room with quiet and/or wi-fi access and/or adequate workspace.

The whole camera-on/camera-off question is getting a lot of attention in pedagogical circles. I may want to see faces to track student engagement and slow down or speed up my lecture based on various kinds of feedback. At the same time, people may be shy, want to hide a disability, feel unsafe from stalking or similar behavior, or have religious issues with video representation. I used to teach asynchronous online classes to students who worked at Saudi Aramco, and those female students operated under very different cultural rules compared to what I was more familiar with. Mandating cameras-on there should not be a unilateral or casual call, or anywhere else for that matter.

The digital divide, long remarked-upon but timidly addressed, consists of more than computing and bandwidth. Without public libraries or coffee shops as “third places,” working or learning from “home” should not be understood simply as the replication of prior social interactions. What we hold private, dear, and shared used to be governed in large measure by physical space: architecture professor Christopher Alexander’s A Pattern Language analyzes all manner of structures in terms of privacy gradients among other factors. Now we need to build both the grammar and vocabulary of personal video representation, and perhaps surprisingly this derives heavily from our physical location. Class and other signaling via our clothing, our speech, our transportation, and our diet is familiar. (Some people hate Android phones because their texts show up in green bubbles with limited functionality on Apple devices.) How we will use this new medium for the discourse of social segmentation and hierarchy — and for much else besides — will be fascinating to watch.

Early Indications March 2020: The Coronavirus hits higher education

After what might have been the weirdest month of my life (I was on a plane to Europe on business 12 days after 9/11, whereas now most of us will be on lockdown for months), much remains uncertain about the world’s economy, politics, livelihoods, and of course sickness and health. Not wishing to join the chorus of people who claim overnight expertise in public health and epidemiology, I can say a little bit about how fast the world of higher education has been upended.

Let’s start with instruction. Obviously colleges and universities are moving to online course delivery fast and furiously. This process relies on software: content management systems were sub-branded learning management systems, and one LMS recently instructed its instructors to call it a Digital Learning Platform. Then there are video bolt-ons, Zoom being the flavor of the month — except for that part where it sells user information to Google et al. Overall, online instruction seems to work really well except when it doesn’t: labs, studio courses, and testing are hard to get right. In addition, student privacy in the US has its equivalent of HIPAA called FERPA, and lots of online tools being pressed into service (Facebook Live?) lack the necessary protections when student IDs and other PII are exchanged, as in a testing scenario. Going forward, we will hear from rural people who lack broadband for online learning, telework, and telemedicine: synchronous video can be finicky and lost frames/speech are quickly frustrating. Our dean wisely advised us to prepare for low-bandwidth scenarios, which fortunately seem not to have materialized in the US (overseas is another story).

The virus's effect on research will be fascinating to track: there are so many conflicting forces emerging. Pro: people have more time in solitude to think and write. Con: it's hard to maintain concentration on research when existential questions -- Central Park hosts a field hospital; predicting 200,000 U.S. deaths constitutes optimism -- confront us daily. (The Stones' "Gimme Shelter" and Talking Heads' "Life During Wartime" are in heavy mental rotation around here.) Pro: there are so many natural experiments running before our eyes, from air pollution measurements to industrial policy to cell-phone tracking of people under various levels of lockdown. Con: labs are closed or staffed only minimally for animal feeding and such. Pro: the virtual infrastructure seems to be performing admirably to deliver needed resources, whether compute cycles or network uptime. Con: student workers including research assistants are pretty much barred from campus. Pro: libraries are offering a lot of services over the wire, though most work with archives and artifacts is halted. Con: academic travel and meetings are shut down. Pro: academic travel and meetings are shut down. Overall, the research output of the next few years will be informed by this chapter of epidemiological history in ways nobody can foresee.

It’s a tough year to be a graduating senior. Internship and job offers can’t really be extended if the hiring company is closed and/or losing money. Students in the travel and hospitality fields, the arts, and retail (Macy’s just furloughed 130,000 people yesterday; TJX has closed more than 4,000 stores worldwide) will be desperate, but even big manufacturers like Boeing and GM face huge uncertainty. Accounting/consulting as a field is rapidly adapting to work from home, raising the question of client-site travel down the road. I doubt it will rebound to previous levels as both managers and clients identify areas for lifestyle improvement and cost savings with no loss of service quality. Given such dismal job prospects, MBA admissions would stand to improve: applications often run counter-cyclically as people step out of a bad labor market to improve skills and earning prospects. Given the timing of this pandemic, that effect -- if there is one -- won't show until September 2021.

Late winter is the culmination of hiring season in many academic disciplines, and new PhDs are usually flying to various on-campus presentations and interviews in January-March. Absent flights, these proceedings are harder to move to video modes of interaction: taking the candidate out to dinner often reveals important cues about his or her cultural fit with the institution. Also in the travel vein, we see hundreds of academic conferences being cancelled or postposed. These are also important in some hiring processes as schools can see as many job candidates as they want at the big professional meetings (the American Psychological Association meeting sees 10,000+ attendees). Doctoral workshops, catching up with colleagues, and networking all are more difficult in a video scenario, which some groups are piloting as we speak. Papers will still get published, albeit without the often valuable feedback one can get in a live room. Also, I recently witnessed our first-ever online PhD defense that went extremely smoothly, so established academic practices are already adapting.

For sake of argument assume a new PhD made her flight to the school that wanted to hire her before everything shut down: I’m hearing of schools that are already rescinding offers. Other departments’ offers are being honored, but all their other in-process searches are being cancelled or frozen. The reason for this is university finances, which are about to be stress-tested to the extreme. Here’s how.

New York is but one state that is delaying state income tax filing because of the pandemic. This delays the state’s budgeting process. Without budgets in the summer, state colleges and universities don’t know what they will have to spend in the academic fiscal year that starts July 1 or thereabouts. (Wild guess: it will be less than last year.) It gets worse. Many schools are issuing refunds of room and board after campuses were closed. This was far from expected: one university official said on the record that Penn State’s liability is more than $40 million. Furthermore, many schools in the US have cultivated pipelines of international students, particularly from China and India. With the combination of travel bans on potentially both sides of the trans-Pacific flight, those tuition dollars might not make it to campus for the fall semester (if there is an in-residence fall semester). The University of Iowa is particularly dependent on China, but fell out of favor last year for a variety of reasons. The University of Illinois, meanwhile, has a $424,000 policy with Lloyds of London to insure against the loss of $60 million from Chinese business and engineering students who cannot attend for specified reasons (pandemics may or may not be on the list.) For their part, Iowa could be in very deep yogurt this fall, and they are not alone. According to Moody’s, about 30% of US colleges and universities, both public and private, were operating at a deficit before Covid-19. Only 5% of private institutions had 90 days of cash on hand. 

Stateside, the US is witnessing the single biggest spike in unemployment claims in history. How many parents or grandparents will pull financial support from a student come fall? Students on scholarship, meanwhile, might be funded by proceeds from a college/university endowment, and with the stock market’s recent tumble, endowment proceeds will come in far below projections. Given family financial hardship, lower state appropriations, and smaller investment returns, budgets will get out of whack pretty quickly. Athletic revenues already took a hit with the cancellation of the NCAA basketball money-fest, and fall football is no sure thing. Precarious liberal-arts colleges, and more already-marginal law schools, will be forced to close.

Markets are often efficient, and it may be time for a culling of the herd given so much oversupply (in law schools, for example). What can we expect as the situation stabilizes? First, instruction will benefit as new hybrid models of face-to-face and online delivery are configured in clever ways. Second, asset utilization will likely improve: expect university real estate to keep its lights on longer, potentially including Saturday classes, in order to contain costs to appeal to cash-strapped families who realize how good virtual instruction can be. Third, as with the world of business and non-profits, professional meetings will increasingly have an online component as everyone sees how good WebEx/Zoom/Teams can be in the crisis. They will become the default for certain kinds of conferencing rather than the exception. The video provider with the best technology, business model, and interoperability could realize dominant market share of a newly huge market. Microsoft squandered Skype’s first-mover advantage; might Teams prove the company’s redemption? Other providers — online testing comes to mind insofar as cheating is a massive issue — will occupy new niches in the hybrid ecosystem. Overall, education is but one locus of what will be a wave of what Schumpeter called “creative destruction.” Where else will old rules be rewritten?