Is AI Just Recycled Intelligence, Which Needs Economics to Help It Along?

The Harvard Data Science Review has just published its first issue. Many of us in economics are cousins of burgeoning data science field, and will find it of interest. As one example, Harvard provost (and economist) Alan Garber offers a broad-based essay on "Data Science: What the Educated Citizen Needs to Know."  Others may be more intrigued by the efforts of Mark Glickman, Jason Brown, and Ryan Song to use a machine learning approach to figure out whether Lennon or McCartney is more likely to have authored certain songs by the Beatles that are officially attributed to both, in "(A) Data in the Life: Authorship Attribution in Lennon-McCartney Songs."

But my attention was especially caught by an essay by Michael I. Jordan called "Artificial Intelligence—The Revolution Hasn’t Happened Yet," which is then followed by 11 comments: Rodney Brooks; Emmanuel Candes, John Duchi, and Chiara Sabatti; Greg Crane; David Donoho; Maria Fasli; Barbara Grosz; Andrew Lo; Maja Mataric; Brendan McCord; Max Welling, and Rebecca Willett.  The rejoinder from Michael I. Jordan will be of particular interest to economists, because it is titled "Dr. AI or: How I Learned to Stop Worrying and Love Economics."

Jordan's main argument is that the term "artificial intelligence" often misleads public discussions, because the actual issue here isn't human-type intelligence. Instead, a set of computer programs that can use data to train themselves to make predictions--what the experts call "machine learning," defined as "an algorithmic field that blends ideas from statistics, computer science and many other disciplines to design algorithms that process data, make predictions, and help make decisions." Consumer recommendation or fraud detection systems, for example, are machine learning, not  the high-level flexible cognitive capacity that most of us mean by "intelligence." As Jordan argues, the information technology that would run, say, an operational system of autonomous vehicles is more closely related to a much more complicated air traffic control system than to the human brain.

(One implication here for economics is that if AI is really machine learning, and machine learning is about programs that can update and train themselves to make better predictions, then one can analyze the effect of AI on labor markets by looking at specific tasks within various jobs that involve prediction. Ajay Agrawal, Joshua S. Gans, and Avi Goldfarb take this approach in "Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction" (Journal of Economic Perspectives, Spring 2019, 33 (2): 31-50). I offered a gloss of their findings in a blog post last month.)

Moreover, the machine learning algorithms, which often involve mixing together results from past research and pre-existing data in different situations with new forms of data can go badly astray. Jordan  offers a vivid example: 

Consider the following story, which involves humans, computers, data, and life-or-death decisions, but where the focus is something other than intelligence-in-silicon fantasies. When my spouse was pregnant 14 years ago, we had an ultrasound. There was a geneticist in the room, and she pointed out some white spots around the heart of the fetus. “Those are markers for Down syndrome,” she noted, “and your risk has now gone up to one in 20.” She let us know that we could learn whether the fetus in fact had the genetic modification underlying Down syndrome via an amniocentesis, but amniocentesis was risky—the chance of killing the fetus during the procedure was roughly one in 300. Being a statistician, I was determined to find out where these numbers were coming from. In my research, I discovered that a statistical analysis had been done a decade previously in the UK in which these white spots, which reflect calcium buildup, were indeed established as a predictor of Down syndrome. I also noticed that the imaging machine used in our test had a few hundred more pixels per square inch than the machine used in the UK study. I returned to tell the geneticist that I believed that the white spots were likely false positives, literal white noise.

She said, “Ah, that explains why we started seeing an uptick in Down syndrome diagnoses a few years ago. That’s when the new machine arrived.”

We didn’t do the amniocentesis, and my wife delivered a healthy girl a few months later, but the episode troubled me, particularly after a back-of-the-envelope calculation convinced me that many thousands of people had gotten that diagnosis that same day worldwide, that many of them had opted for amniocentesis, and that a number of babies had died needlessly. The problem that this episode revealed wasn’t about my individual medical care; it was about a medical system that measured variables and outcomes in various places and times, conducted statistical analyses, and made use of the results in other situations. The problem had to do not just with data analysis per se, but with what database researchers call provenance—broadly, where did data arise, what inferences were drawn from the data, and how relevant are those inferences to the present situation?

The comment by David Donoho refers to this as "recycled intelligence." Donoho writes:

The last decade shows that humans can record their own actions when faced with certain tasks, which can be recycled to make new decisions that score as well as humans’ (or maybe better, because the recycled decisions are immune to fatigue and impulse). ... Recycled human intelligence does not deserve to be called augmented intelligence. It does not truly augment the range of capabilities that humans possess. ... Relying on such recycled intelligence is risky; it may give systematically wrong answers ..."

Donoho offers the homely example of spellcheck programs which, for someone who is an excellent and careful speller, are as likely to create memorable errors as to improve the text.

From Jordan's perspective, what we should be talking about is not whether AI or machine learning will "replace" workers, but instead thinking about how humans will interact with these new capabilities. I'm not just thinking of worker training here, but of the issues related to privacy, access to technology, the structure of market competition, and other issues. Indeed, Jordan argues that one major ingredient missing from the current machine-learning programs is a fine-grained sense of what specific people want--which implies a role for markets. Jordan argues that rather than pretending that we are mimicking human "intelligence," with all the warts and flaws that we know human intelligence has, we should instead be thinking about interactions of how information technology can address the allocation of public and private resources in ways that benefit people. I can't figure out a way to summarize his argument in brief, without doing violence to it, so I quote here at length: 

Let us suppose that there is a fledgling Martian computer science industry, and suppose that the Martians look down at Earth to get inspiration for making their current clunky computers more ‘intelligent.’ What do they see that is intelligent, and worth imitating, as they look down at Earth?

They will surely take note of human brains and minds, and perhaps also animal brains and minds, as intelligent and worth emulating. But they will also find it rather difficult to uncover the underlying principles or algorithms that give rise to that kind of intelligence——the ability to form abstractions, to give semantic interpretation to thoughts and percepts, and to reason. They will see that it arises from neurons, and that each neuron is an exceedingly complex structure——a cell with huge numbers of proteins, membranes, and ions interacting in complex ways to yield complex three-dimensional electrical and chemical activity. Moreover, they will likely see that these cells are connected in complex ways (via highly arborized dendritic trees; please type "dendritic tree and spines" into your favorite image browser to get some sense of a real neuron). A human brain contains on the order of a hundred billion neurons connected via these trees, and it is the network that gives rise to intelligence, not the individual neuron.

Daunted, the Martians may step away from considering the imitation of human brains as the principal path forward for Martian AI. Moreover, they may reassure themselves with the argument that humans evolved to do certain things well, and certain things poorly, and human intelligence may be not necessarily be well suited to solve Martian problems.

What else is intelligent on Earth? Perhaps the Martians will notice that in any given city on Earth, most every restaurant has at hand every ingredient it needs for every dish that it offers, day in and day out. They may also realize that, as in the case of neurons and brains, the essential ingredients underlying this capability are local decisions being made by small entities that each possess only a small sliver of the information being processed by the overall system. But, in contrast to brains, the underlying principles or algorithms may be seen to be not quite as mysterious as in the case of neuroscience. And they may also determine that this system is intelligent by any reasonable definition—it is adaptive (it works rain or shine), it is robust, it works at small scale and large scale, and it has been working for thousands of years (with no software updates needed). Moreover, not being anthropocentric creatures, the Martians may be happy to conceive of this system as an ‘entity’—just as much as a collection of neurons is an ‘entity.’

Am I arguing that we should simply bring in microeconomics in place of computer science? And praise markets as the way forward for AI? No, I am instead arguing that we should bring microeconomics in as a first-class citizen into the blend of computer science and statistics that is currently being called ‘AI.’ ... 

Indeed, classical recommendation systems can and do cause serious problems if they are rolled out in real-world domains where there is scarcity. Consider building an app that recommends routes to the airport. If few people in a city are using the app, then it is benign, and perhaps useful. When many people start to use the app, however, it will likely recommend the same route to large numbers of people and create congestion. The best way to mitigate such congestion is not to simply assign people to routes willy-nilly, but to take into account human preferences—on a given day some people may be in a hurry to get to the airport and others are not in such a hurry. An effective system would respect such preferences, letting those in a hurry opt to pay more for their faster route and allowing others to save for another day. But how can the app know the preferences of its users? It is here that major IT companies stumble, in my humble opinion. They assume that, as in the advertising domain, it is the computer's job to figure out human users' preferences, by gathering as much information as possible about their users, and by using AI. But this is absurd; in most real-world domains—where our preferences and decisions are fine-grained, contextual, and in-the-moment—there is no way that companies can collect enough data to know what we really want. Nor would we want them to collect such data—doing so would require getting uncomfortably close to prying into the private thoughts of individuals. A more appealing approach is to empower individuals by creating a two-way market where (say) street segments bid on drivers, and drivers can make in-the-moment decisions about how much of a hurry they are in, and how much they're willing to spend (in some currency) for a faster route.

Similarly, a restaurant recommendation system could send large numbers of people to the same restaurant. Again, fixing this should not be left to a platform or an omniscient AI system that purportedly knows everything about the users of the platform; rather, a two-way market should be created where the two sides of the market see each other via recommendation systems.

It is this last point that takes us beyond classical microeconomics and brings in machine learning. In the same way as modern recommendation systems allowed us to move beyond classical catalogs of goods, we need to use computer science and statistics to build new kinds of two-way markets. For example, we can bring relevant data about a diner's food preferences, budget, physical location, etc., to bear in deciding which entities on the other side of the market (the restaurants) are best to connect to, out of the tens of thousands of possibilities. That is, we need two-way markets where each side sees the other side via an appropriate form of recommendation system.

From this perspective, business models for modern information technology should be less about providing ‘AI avatars’ or ‘AI services’ for us to be dazzled by (and put out of work by)—on platforms that are monetized via advertising because they do not provide sufficient economic value directly to the consumer—and more about providing new connections between (new kinds of) producers and consumers.

Consider the fact that precious few of us are directly connected to the humans who make the music we listen to (or listen to the music that we make), to the humans who write the text that we read (or read the text that we write), and to the humans who create the clothes that we wear. Making those connections in the context of a new engineering discipline that builds market mechanisms on top of data flows would create new ‘intelligent markets’ that currently do not exist. Such markets would create jobs and unleash creativity.

Implementing such platforms is a task worthy of a new branch of engineering. It would require serious attention to data flow and data analysis, it would require blending such analysis with ideas from market design and game theory, and it would require integrating all of the above with innovative thinking in the social, legal, and public policy spheres. The scale and scope is surely at least as grand as that envisaged when chemical engineering was emerging as a way to combine ideas from chemistry, fluid mechanics, and control theory at large scale.

Certainly market forces are not a panacea. But market forces are an important source of algorithmic ideas for constructing intelligent systems, and we ignore them at our peril. We are already seeing AI systems that create problems regarding fairness, congestion, and bias. We need to reconceptualize the problems in such a way that market mechanisms can be taken into account at the algorithmic level, as part and parcel of attempting to make the overall system be ‘intelligent.’ Ignoring market mechanisms in developing modern societal-scale information-technology systems is like trying to develop a field of civil engineering while ignoring gravity.

Markets need to be regulated, of course, and it takes time and experience to discover the appropriate regulatory mechanisms. But this is not a problem unique to markets. The same is true of gravity, when we construe it as a tool in civil engineering. Just as markets are imperfect, gravity is imperfect. It sometimes causes humans, bridges, and buildings to fall down. Thus it should be respected, understood, and tamed. We will require new kinds of markets, which will require research into new market designs and research into appropriate regulation. Again, the scope is vast.

I can think of all sorts of issues and concerns to raise about this argument (and I'm sure that readers can do so as well), but I also think the argument has an interesting force and plausibility.   

Raising the Minimum Wage: CBO Weighs in

No proposal to raise the minimum wage can be evaluated without asking "how fast and by how much?" The Congressional Budget Office offers an evaluation of three alternatives in "The Effects on Employment and Family Income of Increasing the Federal Minimum Wage" (July 2019).  CBO considers three proposals: "The options would raise the minimum wage to $15, $12, and $10, respectively, in six steps between January 1, 2020, and January 1, 2025. Under the $15 option, the minimum wage would then be indexed to median hourly wages; under the $12 and $10 options, it would not." (There are some other complexities involving possible subminimum wages for teenage workers, tipped worker, and disables workers, which I won't discuss here.)

One way to understand the result is to compare these proposals with the path of wages in the US economy. The top dashed line shows the (adjusted for inflation) wages of workers at the 25th percentile of the wage distribution. The second dashed line shows the wages of workers at the 10th percentile of the wage distribution. The orange line shows the federal minimum wage under current law, both past and present. The three proposals for raising the minimum wage appear on the far right-hand side of the figure.

An obvious takeaway here is that the minimum wage was roughly equal to the 10th percentile of the income distribution in the 1970s. While the minimum wage has fallen below the 10th percentile since then, it almost rises back to that level after the series of minimum wage increases enacted in 2007. However, the minimum wage has been separating from the 10th percentile wage, and the gap is projected to keep growing under current law.

This general background suggests that in a big picture sense, the consequences of having a minimum wage that rises to, say, $12 per hour, won't be all that different from the past consequences of having a minimum wage that's a little below the 10th percentile of wages. However, an increase up to $15/hour in the federal minimum wage would potentially have a greater effect, outside the historical norm.

Considering the effects of a higher federal minimum wage is also complicated by the fact that so many states and cities have already enacted higher minimum wages. The CBO notes:

As of 2019, 29 states and the District of Columbia have a minimum wage higher than the federal minimum. (Many of those states have boosted their minimum wage in recent years.) The minimum wage is indexed to inflation in 17 of those states, and future increases have been mandated in 6 more. Some localities also have minimum wages higher than the applicable state or federal minimum wage; in San Francisco, for instance, the minimum wage increased to $15.59 per hour as of July 1, 2019, and is adjusted for inflation annually. About 60 percent of all workers currently live in states where the applicable minimum wage is more than $7.25 per hour. And in 2025, about 30 percent of workers will live in states with a minimum wage of $15 or higher, CBO estimates ...

Because of all this state and local activity with higher minimum wages, the argument raising the  federal wage has shifted. It's not as much about a minimum wage for all US workers, as it is about a higher minimum wage for the 40% of US workers where that hasn't already happened. And often, those workers live in lower-wage places where the combined forces of politics and economics haven't yet led to a higher minimum wage.

For illustration, here's are estimates of what percentage of workers would be directly affected by a rise in the minimum wage. Past increases in the minimum wage have typically had a directt effect on 5% of workers or less, and an increase in the federal minimum wage to $10/hour or $12/hour fits in this range, while an increase to $15/hour would be a much larger step. (The hollow circles refer to increases in the minimum wage that were proposed back in 2014 to happen in 2016, but didn't actually take place.)

The effects of a higher minimum wage on employment and wages are affected by lots of factors, including all the ways that employers and worker might react to to such an increase in the short-run and the long run, not just through hiring, but also through decisions related to pricing of products and investment in equipment. There are lots of uncertainties in modelling minimum wage increases. CBO did a review of 11 recent studies, finding some that predict a minimum wage will increase employment while others predict it will decrease employment. Here's a table of the studies, for readers who would like to dig deeper. The elasticity is by how much employment for those directly affected by the minimum wage will change in response to a change in wages of 1% caused by the higher minimum wage. In most studies, but not all, the long-run effect is larger than the short-run effect. 

With these uncertainties duly recognized, here the CBO estimate for a phased-in rise in the minimum wage to $15/hour: 

Under the first option [of raising the minimum wage to $15/hour] according to CBO’s median estimate, about 1.3 million workers who would otherwise be employed would be jobless in an average week in 2025. That decrease would account for 0.8 percent of all workers and 7 percent of directly affected workers who would otherwise earn less than $15 per hour. Wages would rise, however, for 17 million directly affected workers who remained employed and for many of the 10 million potentially affected workers whose wages would otherwise fall slightly above $15 per hour—specifically, between the new federal minimum and that amount plus 50 percent of the increase in their applicable minimum wage. The higher wages for those potentially affected workers might lead to reductions in their employment, but some firms might hire more of those workers as substitutes for lower-paid workers whose wages had increased by larger amounts. Those two factors would roughly offset for those higher-wage workers, CBO anticipates. 

The $15 option would alter employment more for some groups than for others. Almost 50 percent of the newly jobless workers in a given week—600,000 of 1.3 million—would be teenagers (some of whom would live in families with income well above the poverty threshold). Employment would also fall disproportionately among part-time workers and adults without a high school diploma. ...

That net effect is due to the combination of factors described above:

• Real earnings for workers while they remained employed would increase by $64 billion,

• Real earnings for workers while they were jobless would decrease by $20 billion,

• Real income for business owners would decrease by $14 billion, and

• Real income for consumers would decrease by $39 billion.

My own quick take is that an increase in the federal minimum wage to $10/hour or even $12/hour is well within the range of past experience, and the effects are likely to be relatively small. Going to $15/hour is a bigger jump.

In particular, there are states and big parts of the country outside of major metropolitan areas where quite a large share of workers make less than $15/hour. Here are some comparisons from Census Bureau data. In May 2018, for example, the median hourly wage in California as a whole was $20.40. However, the median wage in the San Francisco-Oakland-Hayward metro area was $26/hour, while in the Fresno area the median wage was $16.40/hour. Or if one looks across states, the median hourly wage in Mississippi is $14.70/hour, or in Idaho was $16.47/hour. With a very large and diverse US economy, the effects of a higher federal minimum wage will not be evenly distributed by geography. 

US Multinationals Expand their Foreign-based Research and Development

"For decades, US multinational corporations (MNCs) conducted nearly all their research and development (R&D) within the United States. Their focus on R&D at home helped establish the United States as the unrivaled leader of innovation and technology advances in the world economy. Since the late 1990s, however, the amount of R&D conducted overseas by US MNCs has grown nearly fourfold and its geographic distribution has expanded from a few advanced industrial countries (such as Germany, Japan, and Canada) to many parts of the developing world ..."

Lee G. Branstetter, Britta Glennon, andJ. Bradford Jensen discuss this shift in "The Rise of Global Innovation by US Multinationals Poses Risks and Opportunities" (June 2019, Peterson Institute for International Economics,  Policy Brief 19-9).

Here's the quadrupling in foreign-based R&D by US multinationals in the last couple of decades:

Another measure looks at what share of the patents files by US multinationals are based on cross-border collaboration. It used to be less than 2%; it's now more than 10%--and rising. 

It used to be that almost all the foreign R&D of US multinationals was in five high-income countries Germany, the UK, Japan, Canada, and France.Now, less than half is in those five countries.

The shift here shouldn't be exaggerated. "While US MNCs’ foreign R&D expenditures have increased dramatically, they still conducted about 83 percent of their R&D in the United States in 2015 (down from 92 percent in 1989)."

But the shift is still a real one. Of course, it's driven in part by the fact that US multinationals are building supply chains across borders and selling output in other countries. Emerging market have been growing faster than the US economy in recent decades, and with some stops and starts, will probably continue this pattern of faster "catch-up" growth in the next few decades. Another factor is that an interconnected world economy, research is more likely to cross borders than research in older industries.

Your reaction to US multinationals expanding their overseas R&D efforts may be shaped by whether you are a half-empty or a half-full kind of person. US multinationals accounted for 57% of total US R&D spending in 2015. 

The half-empty concern would be that when US companies shift their R&D overseas, there is a danger of losing US-based technological leadership, with potentially negative consequences for US workers and the US economy. There is a legitimate concern that technology developed outside the US may offer less benefit to the US economy, and may be harder to protect with intellectual property rules.

The half-full response is that centers of technological excellence are developing all around the world, with or without participation by US firms. If US firms wish to stay at the technological cutting edge, they need to  engaged with the researchers and expertise all around the world. not to be separated from it. Also, if US multinationals by basing some of the R&D in other countries, US multinationals are building connections to supply chains and to consumers in those markets. 

"Loyalty to the Nation All the Time, Loyalty to the Government When it Deserves It."

Mark Twain wrote an essay back in 1905 called "The Czar's Soliloquy" (North American Review, Vol. 180.No. DLXXX).  The essay was triggered by a sentence in the London Times, reporting: "After the Czar's morning bath it is his habit to meditate an hour before dressing himself." Twain imagined that the Czar, standing naked in front of a mirror, was for a few moments honest with himself about the injustices and cruelties that he had allowed and perpetrated, and hoped for a better future. Imagining the Czar's words to himself, Twain wrote:

There are twenty-five million families in Russia. There is a man-child at every mother's knee. If these were twenty-five million patriotic mothers, they would teach these man-children daily, saying : "Remember this, take it to heart, live by it, die for it if necessary: that our patriotism is medieval, outworn, obsolete; that the modern patriotism, the true patriotism, the only rational patriotism, is loyalty to the Nation all the time, loyalty to the Government when it deserves it.

On the Fourth of July in particular, it makes me sad to run into people whose patriotism ebbs and flows according to what political party occupies the White House. There ought to be a large and real line between support of whoever who is in government at a particular time, and a broader patriotism. A country is a mixture of people, ideals, geography, history, cultures, and more. It should be possible to love your country, whether your feelings about the government are positive, negative, neutral, ambivalent, or don't-give-a-damn.

James Truslow Adams and the Origins of "The American Dream"

The phrase “the American Dream” was coined by a Pulitzer prize-winning historian named James Truslow Adams in his 1931 book The Epic of America. Truslow described the American Dream in this way (pp. 415-416):

But there has been also the American dream, that dream of a land in which life should be better and richer and fuller for every man, with opportunity for each according to his ability or achievement. It is a difficult dream for the European upper classes to interpret adequately, and too many of us ourselves have grown weary and mistrustful of it. It is not a dream of motor cars and high wages merely, but a dream of social order in which each man and each woman shall be able to attain to the fullest stature of which they are innately capable, and be recognized by others for what they are, regardless of the fortuitous circumstances of birth or position. I once had an intelligent young Frenchman as a guest in New York, and after a few days I asked him what struck him most among his new impressions. Without hesitation he replied, "The way that everyone of every sort looks you right in the eye, without a thought if inequality. Some time ago a foreigner who used to do some work for me, and who had picked up a very fair education, occasionally sat and chatted with me in my study after I had finished my work. One day he said that such a relationship was the great difference between America and his homeland. There, he said, "I would do my work and might get a pleasant word, but I could never sit and talk like this. There is a difference there between social grades which cannot be got over. I would not talk to you there as man to man, but as my employer."

No, the American dream that has lured tens of millions of all nations to our shores in the past century has not been a dream of merely material plenty, though that has doubtless counted heavily. It has been much more than that. It has been a dream of being able to grow to fullest development as man and woman, unhampered by the barriers which had slowly been erected by older civilizations, unrepressed by social orders which had developed for the benefit of classes rather than just for the simple human being of any and every class. And that dream has been realized more fully in actual life here than anywhere else, though very imperfectly even among ourselves.

Adams puts this idea of the "American dream" at the center of his description of telling the American narrative and describing what it means to be an American (p. 174):

If Americanism in the above sense has been a dream, it has also been one of the great realities of American life. It has been a moving force as truly as wheat or gold. It is all that has distinguished American from a mere quantitative comparison in wealth or art or letters or power with the nations of old Europe. It is Americanism, and its shrine has been in the heart of the common man. He may not have done much for American culture in its narrower sense, but in its wider meaning it is he who almost alone has fought to hold fast to the American dream. This is what has made the common man a great figure in the American drama. This is the dominant motif in the American epic.

It seems to me that the American dream is sometimes reduced to the idea of upward economic mobility, and while that's certainly part of the vision, it's useful to remember that Adams meant something considerably broader: not just material well-being, but also the opportunity to shape one's destiny; when social order means less and individuals mean more, when social equality is a common presumption in a way that reaches beyond equal treatment before the law, and when the successes and failures of the country are judged by how they affect everyday people.

George Washington on the Dangers of Political Partisanship

George Washington's Farewell Address in 1796 is perhaps best-remembered today for his advice: "'Tis our true policy to steer clear of permanent Alliances, with any portion of the foreign World." But on this Fourth of July, I felt moved to remember and to reconsider Washington's warnings about how political parties set up false alarms, misrepresent others, agitate the community, and can even lead to foreign influence and corruption.

As a sampler, Washington said:

• "One of the expedients of Party to acquire influence, within particular districts, is to misrepresent the opinions & aims of other Districts."
• "The alternate domination of one faction over another, sharpened by the spirit of revenge natural to party dissention, which in different ages & countries has perpetrated the most horrid enormities, is itself a frightful despotism." 
• "[The spirit of Party] serves always to distract the Public Councils and enfeeble the Public Administration. It agitates the Community with ill founded Jealousies and false alarms, kindles the animosity of one part against another, foments occasionally riot & insurrection. It opens the door to foreign influence & corruption, which find a facilitated access to the government itself through the channels of party passions." 

Here's a fuller quotation:

"One of the expedients of Party to acquire influence, within particular districts, is to misrepresent the opinions & aims of other Districts. You cannot shield yourselves too much against the jealousies & heart burnings which spring from these  misrepresentations. They tend to render Alien to each other those who ought to be bound together by fraternal Affection. ... ...

"I have already intimated to you the danger of Parties in the State, with particular reference to the founding of them on Geographical discriminations. Let me now take a more comprehensive view, & warn you in the most solemn manner against the baneful effects of the Spirit of Party, generally.

"This Spirit, unfortunately, is inseperable from our nature, having its root in the strongest passions of the human Mind. It exists under different shapes in all Governments, more or less stifled, controuled, or repressed; but in those of the popular form it is seen in its greatest rankness and is truly their worst enemy.

"The alternate domination of one faction over another, sharpened by the spirit of revenge natural to party dissention, which in different ages & countries has perpetrated the most horrid enormities, is itself a frightful despotism. But this leads at length to a more formal and permanent despotism. The disorders & miseries, which result, gradually incline the minds of men to seek security & repose in the absolute power of an Individual: and sooner or later the chief of some prevailing faction more able or more fortunate than his competitors, turns this disposition to the purposes of his own elevation, on the ruins of Public Liberty.

"Without looking forward to an extremity of this kind (which nevertheless ought not to be entirely out of sight) the common & continual mischiefs of the spirit of Party are sufficient to make it the interest and the duty of a wise People to discourage and restrain

"It serves always to distract the Public Councils and enfeeble the Public Administration. It agitates the Community with ill founded Jealousies and false alarms, kindles the animosity of one part against another, foments occasionally riot & insurrection. It opens the door to foreign influence & corruption, which find a facilitated access to the government itself through the channels of party passions. Thus the policy and the will of one country, are subjected to the policy and will of another.

"There is an opinion that parties in free countries are useful checks upon the Administration of the Government and serve to keep alive the spirit of Liberty. This within certain limits is probably true--and in Governments of a Monarchical cast Patriotism may look with endulgence, if not with favour, upon the spirit of party. But in those of the popular character, in Governments purely elective, it is a spirit not to be encouraged. From their natural tendency, it is certain there will always be enough of that spirit for every salutary purpose. And there being constant danger of excess, the effort ought to be, by force of public opinion, to mitigate & assuage it. A fire not to be quenched; it demands a uniform vigilance to prevent its bursting into a flame, lest instead of warming it should consume."

Is the Health Care Policy Focus Shifting from Access to Cost?

In my experience, complaints about the system of health care finance over the years almost always began with the lack of universal health insurance coverage, and how many tens of millions of Americans lacked health insurance. Then, somewhat later in the conversation, the high per capita costs of US health care spending might or might not come up.

The Patient Protection and Affordable Care Act of 2010 was a reflection of these priorities. The strength of the legislation was that it increased federal spending by over $110 billion per year to cover an expansion of health insurance for about 22 million people. But in terms of controlling healthc are costs, not much happened. US health care spending was 8/9% of GDP in 1980, 13.4% of GDP in 2000, 17.3% of GDP in 2010 when the legislation passed, 17.9% of GDP for the most recent data in 2017, and projected to hit 19.4% of GDP by 2027 by the Centers for Medicare and Medicaid Services. One can argue back and forth over whether this increase in health care spending as a share of GDP has been worth it, but you can't argue that health care costs have held steady or been reduced.

But there are some glimmerings that health care costs are becoming a more prominent and focal issue. For example, West Health and Gallup published "The U.S. Healthcare Cost Crisis" (March 2019, free registration required to download). Based on a nationally representative survey in January and February of this year, here are some findings:

• "Indeed, when given the choice between a freeze in healthcare costs for the next five years and a 10% increase in household income, 61% of Americans report their preference is a freeze in costs. This sentiment runs inversely to income: Among those low-earners with annual household incomes under $24,000 per year, two-thirds would prefer the rising cost of healthcare be fully curtailed for five years over a pay raise. Even among high-earning households with annual incomes of $180,000 or more, there is majority support for frozen costs over increased wages, which would represent at least another $18,000 per year."
• When asked ""Relative to the quality of care, do you think Americans generally are paying too much, too little, or the right amount for most of the care that they receive from the U.S. healthcare system?" 76% of Americans answer "too much."
• "77% of Americans fear rising healthcare costs will damage the U.S. economy, and 45% fear a major health event will lead to bankruptcy."
• "47% of Americans never know what a visit to the emergency room will cost, and 41% report forgoing care in an emergency department due to cost in the past 12 months."
• "Americans borrowed an estimated $88 billion to pay for healthcare, and 65 million adults report having a health issue but not seeking treatment due to cost in the past 12 months."

Other reports are emphasizing cost reduction, too. I wrote earlier this year about how the Society of Actuaries and Henry J. Kaiser Family Foundation have created Initiative 18/11, where the numbers refer to the fact that the US spends about 18% of GDP on health care and other high-income countries spend about 11%, to consider ways of holding down health care costs. 

Polling by the Kaiser Family Foundation (KFF) finds similar concerns about health care costs, and about a greater level of concern about costs. Ashley Kirzinger  Cailey Muñana, Bryan Wu, and Mollyann Brodie  write in a "Data Note: Americans’ Challenges with Health Care Costs" (June 11, 2019)

Americans have consistently put health care costs at the top of their list when it comes to health care issues they want the government to address and for political candidates to talk about. Prior to the passage of the 2010 Affordable Care Act, politicians spoke frequently about health care during elections with equal attention paid to “health care costs” as “access to coverage.” For example, leading up to the 2008 presidential election, a KFF Health Tracking Poll found that “reducing the cost of health care and insurance” (41 percent) was the top health care issue chosen by voters from a list of possible health care issues, but it was closely followed by “expanding health coverage for the uninsured” (31 percent). Since the implementation of the ACA, health care costs now occupy a tier of their own on the public’s list of pressing health care issues. For example, leading up to the 2018 general election, KFF found at least twice as many voters said they wanted hear candidates talk about health care costs (27 percent) as any other health care issue such as increasing access or decreasing the number of uninsured people (11 percent) or universal coverage (8 percent).

The question of why health care costs are taking on greater importance is overdetermined--that is, it has too many plausible answers. People are worried about health care costs directly. I suspect that over time, people are figuring out that the continually rising premiums for their employer-provide health insurance is eating their pay raise.  For state governments, continually rising Medicaid costs are one of the biggest budget stressors. For the federal government, higher spending on health care programs is a large part of what is driving current and future budget deficit problems (for discussions, see here and here). Also, one of the main stresses on the middle class is a sense that the costs of certain items that play a big role in defining what it means to be middle class--health care, housing, and higher education--are climbing out of reach.

As with any serious problem, there will be some easy, deceptive, and flawed answers on display. For example, waving a magic wand called "single payer" or "Medicare for All" won't avoid a need to make a bunch of hard choices. Every dollar spent on health care represents income to someone, somewhere, and cutting healthcare spending is thus inevitably controversial. For discussions of some of these issues, starting points with a focus on US healthcare spending are "How to Reduce Health Care Costs?" (February 7, 2019) or "Why Does the US Spend More on Health Care Than Other Countries?" (May 14, 2012), or for a discussion with an international focus how countries everywhere are trying to hold down health care costs, see "Wasteful Health Care Spending" (February 23, 2017)