The New Davos Challenge

Jan 17, 2020 Alexander Friedman , Jerry Grinstein, Larry Hatheway, Charles C. Krulak

Alexander Friedman, a co-founder of Jackson Hole Economics, is a former Chief Executive Officer of GAM Investments, Chief Investment Officer of UBS, Chief Financial Officer of the Bill & Melinda Gates Foundation, and White House Fellow.

Jerry Grinstein is a former CEO of Delta Air Lines and Burlington Northern Railroad, and previously served as Chief Counsel to the United States Senate Commerce Committee.

Larry Hatheway, former Chief Economist at UBS and GAM Investments, is a co-founder of Jackson Hole Economics.

Charles C. Krulak is a former Commandant of the US Marine Corps and President of Birmingham-Southern College.

As political leaders and corporate titans gather in Davos, Switzerland, for the World Economic Forum’s annual meeting, they would do well to consider how the abstract ideal of „stakeholder capitalism“ can be translated into reality. The key to changing the behavior of economic and political elites alike is to change what is measured.

DAVOS – The World Economic Forum’s annual flagship meeting this year will focus on how to build a more cohesive and sustainable world. As always, the topic is timely, but also a little abstract. To help give it more concrete form, we have a few proposals to put the prevailing economic model on a better track and focus the discussion. 

First, it is time to overhaul the US tax code to reduce structural wealth inequality. To that end, America should get rid of the “carried-interest” loophole. A provision that was originally intended to encourage long-term investment has become a massive tax break for financiers working in private equity and at hedge funds. Although the 2017 Tax Cuts and Jobs Act placed some limitations on this finance-friendly rule, it remains in place.By the same token, America should do away with the “stepped-up cost basis” loophole, which has become a key way by which the rich avoid taxation when bequeathing their wealth to their heirs.

The Truth About the Trump Economy

Jan 17, 2020 Joseph E. Stiglitz, Project Syndicate

Joseph E. Stiglitz, a Nobel laureate in economics, is University Professor at Columbia University and Chief Economist at the Roosevelt Institute. His most recent book is People, Power, and Profits: Progressive Capitalism for an Age of Discontent.

It is becoming conventional wisdom that US President Donald Trump will be tough to beat in November, because, whatever reservations about him voters may have, he has been good for the American economy. Nothing could be further from the truth.

NEW YORK – As the world’s business elites trek to Davos for their annual gathering, people should be asking a simple question: Have they overcome their infatuation with US President Donald Trump?

Two years ago, a few rare corporate leaders were concerned about climate change, or upset at Trump’s misogyny and bigotry. Most, however, were celebrating the president’s tax cuts for billionaires and corporations and looking forward to his efforts to deregulate the economy. That would allow businesses to pollute the air more, get more Americans hooked on opioids, entice more children to eat their diabetes-inducing foods, and engage in the sort of financial shenanigans that brought on the 2008 crisis.

Governments are rethinking the provision of public housing

Date: 16‑01‑2020

Source: The Economist

Is it better to give people money or build them houses?

In the past ten years the homeless population in Los Angeles has risen by 50%. In New York it is 60% up over the same period. San Francisco is widely thought to have America’s worst homelessness problem. Just metres from the headquarters of Twitter and Uber, people lie in the street, stupefied, or defecate in front of the passing traffic. The term “housing crisis” is bandied about too readily. But it is an apt way of describing what is happening in America’s most prosperous cities.

It does not have to be this way. Tokyo is as much a global city as San Francisco, yet you can go days without seeing a single person living on the streets. The inhabitants of Zug, a short drive from Zurich, are as rich as the local Kirschtorte. Astonishing wealth, a waterside location and lots of high‑tech firms mean that Zug bears more than a passing resemblance to San Francisco. But in Zug there is practically no rough sleeping.

Dethroning the dollar

Date: 16‑01‑2020

Source: The Economist

America is weaponising its currency and financial system

Its use of sanctions could endanger the dollar in the long term

Ever since the dollar cemented its role as the world’s dominant currency in the 1950s, it has been clear that America’s position as the sole financial superpower gives it extraordinary influence over other countries’ economic destinies. But it is only under President Donald Trump that America has used its powers routinely and to their full extent, by engaging in financial warfare. The results have been awe‑inspiring and shocking. They have in turn prompted other countries to seek to break free of American financial hegemony.

In 2018 America’s Treasury put legal measures in place that prevented Rusal, a strategically important Russian aluminium firm, from freely accessing the dollar‑based financial system—with devastating effect. Overnight it was unable to deal with many counterparties. Western clearing houses refused to settle its debt securities. The price of its bonds collapsed (the restrictions were later lifted). America now has over 30 active financial‑ and trade‑sanctions programmes. On January 10th it announced measures that the treasury secretary, Steven Mnuchin, said would “cut off billions of dollars of support to the Iranian regime”. The State Department, meanwhile, said that Iraq could lose access to its government account at the Federal Reserve Bank of New York. That would restrict Iraq’s use of oil revenues, causing a cash crunch and flattening its economy.

Different views of AI fuel distrust between China and America

Date: 16‑01‑2020

Source: The Economist: Chaguan

The two countries talk past each other about its risks

In the depths of the cold war, American and Soviet arms‑control negotiators pulled off something remarkable: an agreement so grimly logical that their mutual distrust did not matter. The superpowers pledged to stop building new systems to defend their respective homelands against nuclear missiles. Their Anti‑Ballistic Missile Treaty rested on a theory of mutual deterrence: the notion that the surest path to nuclear‑armed co‑existence lay in knowing that war would lead to catastrophe for both sides.

Today the rivalry between America and China is sliding into its own ice age of suspicion. Once again, new and unproved technologies—this time computer systems capable of performing superhuman tasks using machine learning and other forms of artificial intelligence (ai)—threaten to destabilise the global “strategic balance”, by seeming to offer ways to launch a knockout blow against a nuclear‑armed adversary, without triggering an all‑out war.

A report issued in November by America’s National Security Commission on Artificial Intelligence, a body created by Congress and chaired by Eric Schmidt, a former boss of Google, and Robert Work, who was deputy defence secretary from 2014‑17, ponders how ai systems may reshape global balances of power, as dramatically as electricity changed warfare and society in the 19th century. Notably, it focuses on the ability of ai to “find the needle in the haystack”, by spotting patterns and anomalies in vast pools of data. In a medical setting ai can find tumours that radiologists miss. In a military context, it may one day find the stealthiest nuclear‑armed submarines, wherever they lurk. The commission is blunt. Nuclear deterrence could be undermined if ai‑equipped systems succeed in tracking and targeting previously invulnerable military assets. That in turn could increase incentives for states, in a crisis, to launch a devastating pre‑emptive strike. China’s rise as an ai power represents the most complex strategic challenge that America faces, the commission adds, because the two rivals’ tech sectors are so entangled by commercial, academic and investment ties.

Italy’s second city shows up the rest of the country

Date: 16‑01‑2020

Source: The Economist

Once dismissed for its dullness, Milan is booming

Mariateresa giussani lives in Seregno, 28km (17 miles) outside Milan, and drives to work in the central fashion district where the company she owns, which markets school uniforms, has its offices. “Ten years ago I would leave at 7.15am to avoid the traffic,” she says. “Now, I have to be out by 6.15am. If I leave ten minutes later, it’s nose‑to‑tail all the way.”

Ms Giussani’s altered morning schedule is among the myriad side effects of a boom that has set Milan apart from the rest of Italy, still struggling to recover from the financial crisis of a decade ago, and at best plodding along on the edge of recession.

“The city is on an enormous upswing,” says James Bradburne, the Canadian‑born director of Milan’s most renowned art museum, the Pinacoteca di Brera. Between 2014 and 2018, according to the regional bosses’ federation, Assolombardo, Milan’s output grew by 9.7%—more than twice the national rate. Property prices have leapt. Stories abound of out‑of‑towners paying €400 ($446) a week to rent a single room, residents offered 50% more than they paid for properties bought four years earlier and luxury‑goods firms paying €1m a year or more for an outlet in the Galleria Vittorio Emanuele II, which links La Scala theatre to the cathedral square.

What Could Spoil 2020?

Jan 16, 2020 Anatole Kaletsky, Project Syndicate

Anatole Kaletsky is Chief Economist and Co-Chairman of Gavekal Dragonomics. A former columnist at the Times of London, the International New York Times and the Financial Times, he is the author of Capitalism 4.0: The Birth of a New Economy in the Aftermath of Crisis, which anticipated many of the post-crisis transformations of the global economy. His 1985 book, Costs of Default, became an influential primer for Latin American and Asian governments negotiating debt defaults and restructurings with banks and the IMF.

The most probable scenario for the global economy and financial markets this year is fairly obvious: continued GDP growth, rock-bottom interest rates, and rising equity prices. It’s more useful to identify which unlikely events would alter this likely benign scenario – and consider how unlikely they really are.

LONDON – The traditional January game of economic forecasting for the year ahead hardly seems worth playing when the predictions have been the same for a decade. In 2020, it is even more likely than it has been every year since the financial crisis that the global economy will continue growing, interest rates will remain at rock-bottom levels, and stock markets will keep rising. 

It’s a war between technology and a donkey‘ – how AI is shaking up Hollywood

Date: 16‑01‑2020

Source: The Guardian Steve Rose

Subject: ‚It’s a war between technology and a donkey‘ – how AI is shaking up Hollywood

The film business used to run on hunches. Now, data analytics is far more effective than humans at predicting hits and eliminating flops. Is this a brave new world – or the death knell of creativity?

Cinelytics claims its AI, used by Warner Bros, can forecast box office results with 85% accuracy.

If Sunspring is anything to go by, artificial intelligence in film‑making has some way to go. This short film, made as an entry to Sci‑Fi London’s 48‑hour film‑making competition in 2016, was written entirely by an AI. The director, Oscar Sharp, fed a few hundred sci‑fi screenplays into a long short‑term memory recurrent neural network (the type of software behind predictive text in a smartphone), then told it to write its own. The result was almost, but not quite, incoherent nonsense, riddled with cryptic nonsequiturs, bizarre turns of phrase and unfathomable stage directions such as “he is standing in the stars and sitting on the floor”. All of which Sharp and his actors filmed with sincere commitment.

“In a future with mass unemployment, young people are forced to sell blood,” says a man in a shiny gold jacket. “You should see the boy and shut up. I was the one who was going to be a hundred years old,” replies a woman fiddling with some electronics. The man vomits up an eyeball. A second man says: “Well, I have to go to the skull.” And so forth. An unwitting viewer might be unsure whether they were watching meaningless nonsense or a lost Tarkovsky script.

https://www.youtube.com/watch?time_continue=28&v=LY7x2Ihqjmc&feature=emb_logo

This isn’t how artificial intelligence is changing the movies – yet. But AI is changing the industry in other ways, to a greater extent than is being admitted. In early January, Warner Bros broke cover and announced it had signed up to an AI‑driven project management system that would “inform decision‑making around content and talent valuation to support release strategies”. In other words, Warners will be using AI to help it decide what movies to make.

The system in question was launched last year by Cinelytic, a Los Angeles‑based startup. Other clients listed on its website include Sony Pictures, Ingenious Media and STX Entertainment (the studio behind Hustlers and Playmobil: The Movie). Meanwhile, 20th Century Fox has partnered with Google to develop its own AI, named Merlin, which predicts audiences based on analysis of patterns and objects in movie trailers. Other new companies have also entered the AI game in the past few years, including Belgium‑based ScriptBook and Israel’s Vault AI.

You can see the appeal, especially for a studio like Warner Bros. As well as putting out hits such as Joker and A Star Is Born, it has had its share of box‑office flops, such as King Arthur: Legend of the Sword, The Kitchen, Shaft and The Goldfinch. These projects must have looked like hits on paper. How to tell the difference? Traditionally, Hollywood almost prides itself on its own unpredictability, accepting as a given William Goldman’s adage “no one knows anything”. It is an industry that carries out extensive analysis, research and audience testing, but that still relies to a large extent on human intuition and gut instinct. It is also an industry where the majority of films made are never released, and less than half of those that are make their money back.

Can the machines do better? Absolutely, says Cinelytic, which claims an accuracy of 85% in its box office forecasting. Cinelytic was founded in 2015 by Tobias Queisser, whose background is in finance and film producing. His co‑founder, Dev Sen, is a rocket scientist who developed risk assessment software for Nasa. Cinelytic claims to have crunched data from more than 95,000 movies and 500,000 actors and professionals, but its chief selling point is that it can make forecasts in real time – expressed as percentage probabilities of certain levels of success. With its user‑friendly interface, clients can play with the variables and assess the impact on box office right away.

Let’s make an action comedy starring Dwayne Johnson, say. It will be huge! But what if Johnson is not available? How would it look if you cast Gerard Butler instead? Not so huge, perhaps, but the budget might also be lower. How would it do if you released it over 1,000 screens, or 3,000? How would it do in Brazil or China? In effect, Cinelytic’s AI treats the movie industry like fantasy football, assigning quantitative scores to individuals, according to factors such as recent or past box‑office performance or social media profile.

Others take a slightly different approach. ScriptBook’s AI primarily analyses scripts, as opposed to actors or directors. “Most people believe that cast is everything, but we’ve learned that the story has the highest predictive value,” says Nadira Azermai, who founded the company in 2015. It doesn’t take a computer‑sized brain to think of a movie that had a stellar cast but still flopped. But a good story will succeed even without stars – and potentially more so with them, she says.

Within six minutes, ScriptBook’s AI reads a script and assigns it more than 400 parameters. “Anything that is information: emotion analysis, the journey for the protagonist and antagonist, whether the film will cater to a wide audience or niche audience, whether it follows a traditional three‑act structure, whether the action happens in the most important places.” As more information becomes available, such as the cast, the prediction becomes more accurate, but if the computer says no to begin with, no additional information will change it to a yes.

ScriptBook’s success rates are comparable to those of Cinelytic: 83% to 86%, Azermai claims, whereas human decision‑making is successful 27% to 31% of the time. In a retroactive study of Sony’s output between 2015 and 2017, for example, it successfully identified 22 out of its 32 releases that lost money. It could have saved the company a fortune. It has achieved similar levels of accuracy with movies before they were released, even predicting the success of unconventional outliers such as Get Out, La La Land and A Quiet Place. Azermai is not yet at liberty to reveal which companies ScriptBook has been working with, but she applauds Warners’ announcement that it is working with Cinelytic. “It is an important message, because the majority of companies are still treating AI as a dirty little secret.”

One of the factors driving the AI revolution is undoubtedly Netflix, which, by its spectacular ascent over the past decade, has awakened the entertainment industry to the awesome power of data. Netflix has valued its “recommendations” algorithms (which suggest to viewers what to watch next) at $1bn (£760m) a year in terms of keeping subscribers engaged. The company is notoriously secretive about its methods, but it is safe to assume it is tracking viewers’ every move: what they watch, how long they watch it, what time of day it is, what they watch next, how many hits a new show receives in its first day, and so on. Because Netflix also streams other people’s content, it is even better informed when it comes to producing its own. The studio’s staggering output (Netflix put out 700 original TV shows and 80 features in 2018) would not be possible without AI assistance. As a result of Netflix’s success, tech companies such as Apple and Amazon are getting into content creation and giving the old‑school studios a run for their money.

“All of a sudden you have this conservative, traditional industry versus companies who are believers in data,” says Azermai. “There is a war on content, but one party is using the latest technology and the other is riding a donkey.”

The AI revolution will clearly benefit film‑makers, but what is in it for us viewers? One potential drawback is that AI eliminates not only financial risk but creative risk, too. The fear is, if you fed in a vaguely challenging or experimental or atypical project into the machine – say Mulholland Drive or Under the Skin – the algorithm would discourage you from taking the gamble. Why not do a Dwayne Johnson action comedy instead?

Added to which, the data these algorithms are processing are actually human beings, who are inherently erratic, fallible and unpredictable. Your asset might go into rehab, get divorced or decide to go off and make shoes for a year. In 1996 Robert Downey Jr was arrested driving his Porsche naked through Los Angeles throwing imaginary rats out of the window. What algorithm would have recommended casting him as Iron Man?

“Already we’re seeing that we’re getting more and more remakes and sequels because that’s safe, rather than something that’s out of the box,” says Tabitha Goldstaub, a tech entrepreneur and commentator who specialises in artificial intelligence. Her work has raised deeper concerns about AI. Far from being a dispassionate tool, it often reflects the biases and prejudices of its creators, she says. “A lot of people think it’s maths so it can’t be biased, whereas in fact it’s completely the opposite way around: it’s maths, and therefore it’s data, and whatever data you feed a machine will have bias in it. The world is biased, and so these machines exacerbate our own biases.”

She points to the fact that no women have been nominated for best director at this year’s Oscars, and only five women have ever been nominated. The AI might well conclude that if you want to make an Oscar‑winning movie, don’t hire a female director. “You can’t help but think: do you really want to leave these people in charge of creating an algorithm that predicts the next hits? It’s quite scary.”

But there are signs that AI could help reduce bias. The producer Todd Garner cited an example on his Producer’s Guide podcast recently. Garner’s company produced the Marlon Wayans comedies White Chicks and Little Man, and did very well out of them. But when it took a new Wayans project to traditional studios and financiers, nobody bit, he says. “Because there was no way, they thought, that this movie would play internationally … so it’s a purely domestic play [a US‑only release]. Netflix came in and scooped it up immediately, gave us a lot more money to make the movie and the movie was huge for their site. Because Netflix had hosted White Chicks and other Wayans movies on their site, they knew that Marlon Wayans has a worldwide audience. If you don’t have that data, your instinct is, well, African American movies don’t play overseas, period.”

Now that AI is here, there is also the question of how much further it will infiltrate film‑making. Screenwriting, for example. Things have moved on since Sunspring in 2016. Last year, Kevin Macdonald directed a one‑minute advert for Lexus entirely written by an AI – that had been trained on 15 years’ worth of luxury ads.

https://www.youtube.com/watch?time_continue=60&v=OxyHuJSM_jI&feature=emb_logo

As well as analytical tools, ScriptBook is developing a screenwriting AI, which it has given the dystopian sci‑fi thriller name of Deepstory. “It really is a co‑creator,” says Azermai, reassuringly. “We envision a next‑generation writers’ room where whenever they don’t know where to head to for the next scene, they would have Deepstory create it. The engine takes into account everything that you’ve written, and it will deliver you the next scene, or the next 10 pages, or write it to the end.” Azermai admits Deepstory still has much to learn. “The consistency in writing stays for another 10 pages and then the AI becomes a bit crazy – sometimes it kills the protagonist for some reason – but it’s improving. Within five years we’ll have scripts written by AI that you would think are better than human writing.”

The movies themselves have trained us to be suspicious of AIs. They make terrible substitute children (Spielberg’s AI), and even worse romantic partners (Spike Jonze’s Her). They often decide humans are expendable and take over (Kubrick’s 2001) or they enslave us in some futuristic dystopia (Terminator, The Matrix). Could it be that by embracing AI, Hollywood is unwittingly building an equivalent of the Terminator movies’ Skynet? Or, in a slightly less apocalyptic scenario, are we looking at a future where movies are personally tailored to individual viewers? Might we be approaching a sort of Turing test for machine‑written fiction? Maybe we have passed it already and we just don’t know it yet. Sounds like a plot for a great, metatextual Hollywood conspiracy thriller. If we got Dwayne Johnson it could be a smash. Let’s crunch some numbers!

 

Has the World Economy Reached Peak Growth?

Jan 16, 2020 Jim O’Neill, Projec Syndicate

Jim O’Neill, a former chairman of Goldman Sachs Asset Management and a former UK Treasury Minister, is Chair of Chatham House.

Whether or not the 2010s were a „lost decade,“ one thing is clear: many countries fell short of their potential, possibly squandering their last best shot of registering strong GDP growth. In the decade ahead, demographic realities will catch up to China and the West, and the world will need a productivity miracle to offset the effects.

LONDON – At the start of a new decade, many commentators are understandably focused on the health of the global economy. GDP growth this decade most likely will be lower than during the teens, barring a notable improvement in productivity in the West and China, or a sustained acceleration in India and the largest African economies.

Until we have final fourth-quarter data for 2019, we won’t be able to calculate global GDP growth for the 2010-2019 decade. Still, it is likely to be around 3.5% per year, which is similar to the growth rate for the 2000s, and higher than the 3.3% growth of the 1980s and 1990s. That slightly stronger performance over the past two decades is due almost entirely to China, with India playing a modestly expanding role.Average annual growth of 3.5% for 2010-2019 means that many countries fell short of their potential.

The trillion‑dollar club: technology stocks

Date: 15‑01‑2020

Source: The Economist

Amazon, Apple and Microsoft have already done it. And this week Alphabet, Google’s parent, is, for the first time, also flirting with a $1trn market capitalisation.

Big Tech shares keep soaring after a banner 2019, which saw the quartet outpace America’s frothy stockmarket.

Add Facebook, and America’s five biggest companies have gained a cumulative $1.8trn since the start of last year.

Surely, this cannot go on. Or can it? Although the Sino‑American trade war has spilled over into tech and controversies rage at home over abuses of user privacy and market power, the giants keep printing money.

After years of sacrificing profits for investment, even Amazon (poised to rejoin the $1trn gang soon) has generated billions in free cashflow.

Investors reckon more of this will be returned to shareholders, starting with Alphabet. A new chief executive, Sundar Pichai, took over from Google’s founders in December. He is expected to be more shareholder‑friendly—and less dividend‑wary.