AI: Replacing managers with automated decision-making saves time and eliminates emotional volatility says world’s largest hedge fund

Bridgewater Associates has a team of engineers working on a project to automate decision-making to save time and eliminate human emotional volatility. See article in The Guardian, below.  

This has an interesting connection to the weather and also air pollution.  The Wall Street Journal, Harvard Business Review and medical researchers had already previous reported that air pollution from fossil fuel combustion can prompt anxiety and depression and affect risk tolerance.  Higher CO2 levels reduce 8 different metrics of human cognition.  

By  | Last updated: December 5, 2016:  When New York is enveloped in pollution, the stock market loses value and sends a negative signal to global markets, a new paper finds.  Air pollution is bad for us, for children’s health and development, and for the global climate. Researchers also have found smog and dirty air associated with diminished work performance and poorer cognitive output in adults.  See “The Effect of Air Pollution on Investor Behavior: Evidence from the S&P 500,” published by the National Bureau of Economic Research, October 2016.  The researchers analyze four types of data across 15 years (2000 to 2014): For equities, they look at returns from the S&P 500 index, a diversified portfolio of companies that often serves as a benchmark for the overall health of the American economy. For pollution, they use EPA data on fine particulate matter (PM2.5) — airborne solids and liquids of less than 2.5 micrometers in diameter. Most PM2.5 emanate from car exhaust and burning fossil fuels for heating and industry. PM2.5 are especially interesting to scientists because they are found indoors as well as outdoors. The authors use the Volatility Index (often known as the “fear gauge”) published by the Chicago Board Options Exchange to chart expected market movement over the next year. Finally, since weather has been associated with market movements, they use EPA weather data as a control.  Heyes and his team also control for other pollutants, time of year and day of the week. They acknowledge that investors are widely dispersed around the globe, but see the “very strong concentration” of market-influencers in New York as indicative of air pollution’s effect. The authors claim to prove causality, not just correlation. 


  • A one standard deviation increase in airborne PM2.5 levels causes an 11.9 percent decrease in that day’s S&P 500 returns (that is not a decrease in the absolute value of the index, but in how the market moved).
  • The PM2.5 effects are immediate.
  • The authors find a relationship between PM2.5 and risk tolerance, “that a one unit increase in PM2.5 concentration increases the value of VIX by 1.9 percent.”
  • The findings can be applied to workers in other occupations in other developed countries and suggest “the detrimental effect of pollution on workplace performance is even more widespread than previously believed.”
  • The findings are also an indicator of how pollution can undermine “the efficient operation of a modern economy. […] Variations in the quality of air in Manhattan systematically distort investment signals being sent out across the whole economy.”

Other research:

  • PM2.5 has a strong impact on indoor worker productivity, found the authors of a 2016 paper in the American Economic Journal: “Particulate Pollution and the Productivity of Pear Packers.”
  • By testing baseball umpires, the authors of this 2016 working paper found cognition sharply decreased even when levels of PM2.5 and carbon monoxide (CO) were below EPA standards.
  • Traders in New York tend to sell stocks when the sky is cloudy at market open and the market is more volatile on cloudy days, the authors of this 2008 paper found.
  • Israeli high school students in areas with higher levels of PM2.5 and CO perform worse on standardized tests compared to peers in cleaner areas, according to this 2014 NBER working paper.
  • Chinese equity markets are negatively impacted for several days after a spike in airborne pollution, this 2016 paper in Applied Economics suggests.

By Olivia Solon, The Guardian,

The Systematized Intelligence Lab is headed by David Ferrucci, who previously led IBM’s development of Watson, the supercomputer that beat humans at Jeopardy! in 2011.
The Systematized Intelligence Lab is headed by David Ferrucci, who previously led IBM’s development of Watson, the supercomputer that beat humans at Jeopardy! in 2011. Photograph: AP

Bridgewater Associates has a team of software engineers working on the project at the request of billionaire founder Ray Dalio, who wants to ensure the company can run according to his vision even when he’s not there, the Wall Street Journal reported.

“The role of many remaining humans at the firm wouldn’t be to make individual choices but to design the criteria by which the system makes decisions, intervening when something isn’t working,” wrote the Journal, which spoke to five former and current employees.

The firm, which manages $160bn, created the team of programmers specializing in analytics and artificial intelligence, dubbed the Systematized Intelligence Lab, in early 2015. The unit is headed up by David Ferrucci, who previously led IBM’s development of Watson, the supercomputer that beat humans at Jeopardy! in 2011.

The company is already highly data-driven, with meetings recorded and staff asked to grade each other throughout the day using a ratings system called “dots”. The Systematized Intelligence Lab has built a tool that incorporates these ratings into “Baseball Cards” that show employees’ strengths and weaknesses. Another app, dubbed The Contract, gets staff to set goals they want to achieve and then tracks how effectively they follow through.

These tools are early applications of PriOS, the over-arching management software that Dalio wants to make three-quarters of all management decisions within five years. The kinds of decisions PriOS could make include finding the right staff for particular job openings and ranking opposing perspectives from multiple team members when there’s a disagreement about how to proceed.

The machine will make the decisions, according to a set of principles laid out by Dalio about the company vision.

“It’s ambitious, but it’s not unreasonable,” said Devin Fidler, research director at the Institute For The Future, who has built a prototype management system called iCEO. “A lot of management is basically information work, the sort of thing that software can get very good at.”

Automated decision-making is appealing to businesses as it can save time and eliminate human emotional volatility.

“People have a bad day and it then colors their perception of the world and they make different decisions. In a hedge fund that’s a big deal,” he added.

Will people happily accept orders from a robotic manager? Fidler isn’t so sure. “People tend not to accept a message delivered by a machine,” he said, pointing to the need for a human interface.

“In companies that are really good at data analytics very often the decision is made by a statistical algorithm but the decision is conveyed by somebody who can put it in an emotional context,” he explained.

Futurist Zoltan Istvan, founder of the Transhumanist party, disagrees. “People will follow the will and statistical might of machines,” he said, pointing out that people already outsource way-finding to GPS or the flying of planes to autopilot.

However, the period in which people will need to interact with a robot manager will be brief.

“Soon there just won’t be any reason to keep us around,” Istvan said. “Sure, humans can fix problems, but machines in a few years time will be able to fix those problems even better.

“Bankers will become dinosaurs.”

It’s not just the banking sector that will be affected. According to a report by Accenture, artificial intelligence will free people from the drudgery of administrative tasks in many industries. The company surveyed 1,770 managers across 14 countries to find out how artificial intelligence would impact their jobs.

However, they didn’t think there was too much cause for concern. “It just means that their jobs will change to focus on things only humans can do.”

The authors say that machines would be better at administrative tasks like writing earnings reports and tracking schedules and resources while humans would be better at developing messages to inspire the workforce and drafting strategy.

Fidler disagrees. “There’s no reason to believe that a lot of what we think of as strategic work or even creative work can’t be substantially overtaken by software.”

However, he said, that software will need some direction. “It needs human decision making to set objectives.”

Bridgewater Associates did not respond to a request for comment.

This robot was initially developed to allow more independence for people with disabilities and is now being used for adjunct child entertainment and care.

Excerpts from

The rise of the useless class

…Until a short time ago, facial recognition was a favorite example of something that babies accomplish easily but which escaped even the most powerful computers. Today, facial-recognition programs are able to identify people far more efficiently and quickly than humans can.

In 2004, professor Frank Levy from MIT and professor Richard Murnane from Harvard published research on the job market, listing those professions most likely to undergo automation. Truck driving was given as an example of a job that could not possibly be automated in the foreseeable future. A mere 10 years later, Google and Tesla can not only imagine this, but are actually making it happen.

…In fact, as time goes by, it becomes easier and easier to replace humans with computer algorithms, not merely because the algorithms are getting smarter, but also because humans are professionalizing. Ancient hunter-gatherers mastered a very wide variety of skills in order to survive, which is why it would be immensely difficult to design a robotic hunter-gatherer.

For AI to squeeze humans out of the job market it need only outperform us in the specific abilities a particular profession demands.

As algorithms push humans out of the job market, wealth and power might become concentrated in the hands of the tiny elite that owns the all-powerful algorithms, creating unprecedented social and political inequality… most of our planet is already legally owned by non-human intersubjective entities, namely nations and corporations. Indeed, 5,000 years ago much of Sumer was owned by imaginary gods such as Enki and Inanna. If gods can possess land and employ people, why not algorithms?

In the 19th century the Industrial Revolution created a huge urban proletariat, and socialism spread because no other creed managed to answer the unprecedented needs, hopes and fears of this new working class. Liberalism eventually defeated socialism only by adopting the best parts of the socialist program. In the 21st century we might witness the creation of a massive new unworking class: people devoid of any economic, political or even artistic value, who contribute nothing to the prosperity, power and glory of society. This “useless class” will not merely be unemployed — it will be unemployable.

In September 2013, two Oxford researchers, Carl Benedikt Frey and Michael A. Osborne, published “The Future of Employment,” in which they surveyed the likelihood of different professions being taken over by computer algorithms within the next 20 years, and they estimated that 47 percent of US jobs are at high risk. For example, there is a 99 percent probability that by 2033 human telemarketers and insurance underwriters will lose their jobs to algorithms. There is a 98 percent probability that the same will happen to sports referees. Cashiers — 97 percent. Chefs — 96 percent. Waiters — 94 percent. Paralegals — 94 percent. Tour guides — 91 percent. Bakers — 89 percent. Bus drivers — 89 percent. Construction laborers — 88 percent. Veterinary assistants — 86 percent. Security guards — 84 percent. Sailors — 83 percent. Bartenders — 77 percent. Archivists — 76 percent. Carpenters — 72 percent. Lifeguards — 67 percent. There are, of course, some safe jobs. The likelihood that computer algorithms will displace archaeologists by 2033 is only 0.7 percent, because their job requires highly sophisticated types of pattern recognition and doesn’t produce huge profits and it is improbable that corporations or government will make the necessary investment to automate archaeology within the next 20 years.

Most of what kids currently learn at school will probably be irrelevant by the time they are 40.

Of course, by 2033 many new professions are likely to appear — for example, virtual-world designers. But such professions will probably require much more creativity and flexibility than current run-of-the-mill jobs, and it is unclear whether 40-year-old cashiers or insurance agents will be able to reinvent themselves as virtual world designers (try to imagine a virtual world created by an insurance agent!). And even if they do so, the pace of progress is such that within another decade they might have to reinvent themselves yet again. After all, algorithms might well outperform humans in designing virtual worlds, too. The crucial problem isn’t creating new jobs. The crucial problem is creating new jobs that humans perform better than algorithms.

Since we do not know how the job market would look in 2030 or 2040, today we have no idea what to teach our kids. Most of what they currently learn at school will probably be irrelevant by the time they are 40. Traditionally, life has been divided into two main parts: a period of learning, followed by a period of working. Very soon this traditional model will become utterly obsolete, and the only way for humans to stay in the game will be to keep learning throughout their lives and to reinvent themselves repeatedly. Many, if not most, humans may be unable to do so.

The coming technological bonanza will probably make it feasible to feed and support people even without any effort from their side. But what will keep them occupied and content? One answer might be drugs and computer games. Unnecessary people might spend increasing amounts of time within 3D virtual-reality worlds that would provide them with far more excitement and emotional engagement than the drab reality outside. Yet such a development would deal a mortal blow to the liberal belief in the sacredness of human life and of human experiences. What’s so sacred about useless bums who pass their days devouring artificial experiences?

Some experts and thinkers, such as Nick Bostrom (TED Talk: What happens when our computers get smarter than we are?), warn that humankind is unlikely to suffer this degradation, because once artificial intelligence surpasses human intelligence, it might simply exterminate humankind. The AI would likely do so either for fear that humankind would turn against it and try to pull its plug, or in pursuit of some unfathomable goal of its own. For it would be extremely difficult for humans to control the motivation of a system smarter than themselves.

Even preprogramming an AI system with seemingly benign goals might backfire horribly. One popular scenario imagines a corporation designing the first artificial super-intelligence and giving it an innocent test such as calculating pi. Before anyone realizes what is happening, the AI takes over the planet, eliminates the human race, launches a campaign of conquest to the ends of the galaxy, and transforms the entire known universe into a giant supercomputer that for billions upon billions of years calculates pi ever more accurately. After all, this is the divine mission its Creator gave it.

Excerpted from the new book Homo Deus: A brief history of tomorrow by Yuval Noah Harari.