WTF?: What's the Future and Why It's Up to Us

by Tim O'Reilly

History tells us technology kills professions, but does not kill jobs.

This is the true opportunity of technology: It extends human capability.

Despite Silicon Valley’s dreams of a future singularity, an unknowable fusion of minds and machines that will mark the end of history as we know it, what history teaches us is that economies and nations, not just companies, can fail.

Over the past few decades, companies have made a deliberate choice to reward their management and “superstars” incredibly well, while treating ordinary workers as a cost to be minimized or cut.

We are at a very dangerous moment in history. The concentration of wealth and power in the hands of a global elite is eroding the power and sovereignty of nation-states while globe-spanning technology platforms are enabling algorithmic control of firms, institutions, and societies, shaping what billions of people see and understand and how the economic pie is divided. At the same time, income inequality and the pace of technology change are leading to a populist backlash featuring opposition to science, distrust of our governing institutions, and fear of the future, making it ever more difficult to solve the problems we have created.

The biggest changes are still ahead, and every industry and every organization will have to transform itself in the next few years, in multiple ways, or fade away.

understanding the future requires discarding the way you think about the present, giving up ideas that seem natural and even inevitable.

It’s easy to blame technology for the problems that occur in periods of great economic transition. But both the problems and the solutions are the result of human choices.

If we let machines put us out of work, it will be because of a failure of imagination and a lack of will to make a better future.

“Information doesn’t want to be free. Information wants to be valuable.”

The question for me became one of how to maximize value creation for society, rather than simply value capture by an individual or a company.

every year technology products cost less and do more,

Whatever you may think of Uber, it is hard to deny its impact on the economy. If we want to understand the future, we have to understand Uber. Like it or not, it is the poster child for many of the ways that technology is changing the world of work.

Prices must be so low that calling an Uber or Lyft is not just vastly more convenient than owning a car, but more affordable as well.

in a sense, Apple Pay was payments for everyone who hadn’t caught up with the fact that truly disruptive services had already done away with the old payment model.

when marketplaces become digital, they become living systems, neither human nor machine, independent of their creators and less and less under anyone’s control.

every corporation is a kind of hybrid of man and machine, created and operated by humans to augment their individual efforts.

the world has moved on and we are stuck in the past.

once a company reaches monopoly status, it is no longer a marketplace participant. It is the market.

the power of a system comes more from the relationships among programs than from the programs themselves.”

“Lock-in” comes because others depend on the benefit from your services, not because you’re completely in control.

In the digital era, an online service and the organization that produces and manages it must become inseparable.

Jeff’s first key insight was that Amazon could never turn itself into a platform unless it was itself built from the ground up using the same APIs that it would offer to external developers.

the deepest insight about the nature of networked organizations comes from the way that Amazon structured itself internally to match the service-oriented design of its platform.

“Services do not only represent a software structure but also the organizational structure. The services have a strong ownership model, which combined with the small team size is intended to make it very easy to innovate. In some sense you can see these services as small startups within the walls of a bigger company. Each of these services require a strong focus on who their customers are, regardless whether they are externally or internally.”

the classic thick marketplace, where users came for the apps, and apps came for the users.

Big government versus small government is in many ways beside the point. If government is successful as a platform, you could have small government and big services, just like Apple does with the iPhone.

The question shouldn’t be whether or not government ought to be doing these things; it should be how to help government do a better job of fulfilling its responsibilities as a platform.

Simply putting a digital front end on a broken bureaucratic system often only makes the problem worse, because the digital system replicates existing processes without rethinking them from the ground up.

These programs are workers, and the programmers who create them are their managers.

“simple models and a lot of data trump more elaborate models based on less data,”

“We shape our tools, and thereafter our tools shape us.”

Possibly the most important questions in AI are not the design of new algorithms, but how to make sure that the data sets with which we train them are not inherently biased.

Laws should specify goals, rights, outcomes, authorities, and limits. If specified broadly and clearly, those laws can stand the test of time. Regulations, which specify how to execute those laws in much more detail, should be regarded in much the same way that programmers regard their code and algorithms, that is, as a constantly updated set of tools designed to achieve the outcomes specified in the laws.

There are those who say that government should just stay out of regulating many areas, and let “the market” sort things out. But bad actors take advantage of a vacuum in the absence of proactive management. Just as companies like Google, Facebook, Apple, Amazon, and Microsoft build regulatory mechanisms to manage their platforms, government exists as a platform to ensure the success of our society, and that platform needs to be well regulated.

In an age of ubiquitous commercial surveillance that is intrinsic to the ability of companies to deliver on the services we ask for, the kind of privacy we enjoyed in the past is dead.

Disclosure and consent as currently practiced are extraordinarily weak regulatory tools. They allow providers to cloak malicious intent in complex legal language that is rarely read, and if read, impossible to understand.

While there are still risks of bad drivers, and critics have made the most of crimes committed by Uber drivers, the fact that every Uber ride is tracked in real time, with the exact time, location, route, and the identity of both the driver and the passenger known, makes an Uber or Lyft ride inherently safer than a taxi ride.

perhaps we are just living in a new “post-truth” world, where appeals to emotion carry more weight than facts.

“We aren’t fighting our first cyberwar. We just fought it. And we already lost.”

“A lie will have gone halfway around the world before the truth has had time to tie on its shoes.”

The algorithm does not have to find absolute truth; it has to find a reasonable doubt, just like a human jury.

Fake news got a big boost from a flawed algorithm that seems to have favored the emotional rush of partisan engagement over other factors.

the essence of algorithm design is not to eliminate all error, but to make results robust in the face of error.

there was a close correlation between civic engagement and prosperity.

Humans are a fundamentally social species; the tribalism of today’s toxic online culture may be a sign that it is time to reinvent all of our social institutions for the online era.

There is a master algorithm that rules our society, and, with apologies to Pedro Domingos, it is not some powerful new approach to machine learning. It is a rule that was encoded into modern business decades ago, and has largely gone unchallenged since.

We are already in the thrall of a vast, world-spanning machine that, due to errors in its foundational programming, has developed a disdain for human beings, is working to make them irrelevant, and resists all attempts to bring it back under control. It is not yet intelligent or autonomous, and it still depends on its partnership with humans, but it grows more powerful and more independent every day. We are engaged in a battle for the soul of this machine, and we are losing. Systems we have built to serve us no longer do so, and we don’t know how to stop them. If you think I’m talking about Google, or Facebook, or some shadowy program run by the government, you’d be wrong. I’m talking about something we refer to as “the market.”

The fact that we are building financial products that no one understands is actually a reflection of the fundamental design of the modern financial system.

Yes, the markets have become a hybrid of human and machine intelligence. Yes, the speed of trading has increased, so that a human trader not paired with that machine has become prey, not predator.