Artificial Intelligence (AI) may well be the most powerful technology of the 21st century, helping to solve humanity’s most complex unsolved problems: environmental, social, and more.  Yet sceptics believe that AI’s risks are as large as its potential benefits. How can they be avoided? And why isn’t the most powerful technology being used more widely today to solve the world’s greatest “wicked” problems? Great technological advances are often a double-edged sword. A backlash follows an initial “honeymoon period”. Unintended consequences that were not immediately obvious during the technology’s infancy become more apparent, and may even overwhelm the initial, benefits. A historical example is the cotton gin, which led indirectly to the U.S. Civil War.   The challenge is to iron out the rough edges while preserving the benefits. We have been living through a great technological revolution, driven by the ever-increasing capabilities of information systems, and convergence with communications technology.  The byproduct is the widespread availability of unimaginably vast amounts of data. Yet data value is latent at best, unless we have some way to make sense of it. This is where AI fits in: it processes data to produce insights. Yet, today, the “AI honeymoon” is coming to an end, experiencing the first waves of widely recognized unintended consequences. Gathering and analyzing data is, in its way, a new kind of “microscope”, providing insights into human behavior, science, medicine, and more. For instance, a Target grocery store can now famously determine if a girl is pregnant before her parents find out. And the recent controversy around the exploitation of Facebook’s microtargeting capabilities to propagate fake news, with impacts on elections worldwide, raises the prospect that democratic outcomes will be undermined by AI-driven voter-manipulation campaigns. Some even predict that AI poses an existential threat to humanity. So how can we avoid the negatives of AI while maximizing its benefits? Here are some guidelines: Understand that AI today is limited. By far, the majority of successful AI scenarios involve a single “link”. “Here’s a picture of a city street, what does it show?”, “Here’s Joe’s Amazon browsing and purchasing history, what new product will Joe he want next?”, “Here’s a voter, what issues are they most interested in?”, “Here’s information about a medical device, when will it fail”? Know that AI is subject to dangerous biases.  What if, for example, an AI system were to identify that persons of a certain ethnicity were more prone to violence, and therefore should not be allowed into certain housing projects? This may have nothing to do with the real traits of any particular ethnic group, but rather with unseen idiosyncrasies in the training data. But, the AI system can’t tell the difference. The pattern here is insidious: the correlation between race and violence may be well-established in a given data set, but that doesn’t mean that race is the causative factor for the violence: the cause could be historical events that happen to correlate with race. AI systems do not “understand” the world. They don’t find causal connections, only correlations in the data they are presented with. The solution to endemic violence isn’t found by excluding persons of a certain race, but rather by removing the underlying factors that have disproportionately affected people of a certain race. To do this, the near-term future of AI is to map causal links to form a chain from actions to outcomes, and to show how two correlating things may not cause each other “If I invest $X in police and $Y in the legal system, how will that impact crime?”, “If I visit voters in this neighborhood, how much will that help my candidate to be elected?” And multi-link thinking is essential to solving the next set of hard problems in a complex world. More often than not, these links involve “soft” factors, like attitude, empathy, morale, hope, and fear. These chains of events often contain loops that build on each other, in “vicious” and “virtuous” cycles, as shown below. For instance: “Money invested in policing and legal services lead to increased trust in the government, which leads to decreased preemptive violence, which leads to social stability, which leads to business investment, which increases the tax base, which gives us more money for policing and legal services.”, “As more and more of our workforce in this area is sick, they are less able to work, decreasing the tax base, and reducing our ability to invest in health care.” AI alone is not able to determine how these cause-and-effect chains fit together. That requires human expertise, in a hybrid “augmented intelligence” scenario. Data today is pervasive, and AI helps brings value to it. “Multi-link” AI―called Decision Intelligence (DI)―solves the hard AI problems. To reap the greatest benefit from AI, while avoiding its negatives, we need to evolve beyond inward-facing, single-link systems, and use technology to model, as well, the complex causal systems in which they function. About the author: A 35-year AI veteran, Pratt is Chief Scientist at Quantellia, which builds AI/DI systems worldwide, and is cofounder at winworks.ai, which bridges candidates to their constituents.  Pratt was recently recognized as an outstanding Woman Innovator and is known for her pioneering work on transfer learning and decision intelligence Editor's Note: This article was originally published in the print edition of the 2018 G7 Summit magazine.

But it’s difficult to think about value when we have no buoy for understanding it outside our traditional lenses: for example, our time, our job, and what others tell us they are worth in cash. This, largely, is the world’s paradigm for value so far. But understanding what value really means changes everything—and will be at the center of the decentralized revolution in global coordination that will unfold over the next decade. So, where do we begin?

Let’s start with gold.

Gold is an inherent value. When backing a market, gold allows us to grow a balanced economy well into the trillions. But why does it allow for massive stable markets to form around it? It is gold's permanence that creates stability. We understand that gold will always have value, because it is inherent in all of us, not just in one part of the world, but everywhere, not just today, but tomorrow and for the long haul.

In the 1930s when the gold standard was removed, we learned that the U.S. dollar didn’t need gold to back its economy to flourish. We learned that it was just a symbol for U.S. citizens to decentralize their coordination around the United States economy.

It turns out, common agreement is a philosophy for building shared economy.

And so it seems inherent value is a marker for us to begin exploring what the future could look like—a future beyond gold and the existing realm of credit. And so what else has inherent value? Is education as valuable as gold? What about healthcare? What about a vote that can’t be tampered with? What about an ID that can’t be stolen or erased? What about access to nutrition or clean water? You will find value everywhere you look.

It turns out, we’ve already done the legwork necessary to uncover the most elemental inherent values: The Sustainable Development Goals are commitments grown out of the drive to bring to life basic tenets of the Universal Declaration of Human Rights—the closest possible social contract we have to a global, common agreement.

We’ve already agreed, as a global community, to ensure inclusive and equitable access to quality education. We’ve already agreed to empower all women and girls, to ensure pure and clean water access for all, to promote health at all stages of life, and to end hunger.

We’ve already agreed.

Our agreements are grounded in deep value centers that are globally shared, but undervalued and unfulfilled. The reason for this is our inability to quantify intangible value. All of these rich, inherent values are still nebulous and fragmented in implementation—largely existing as ideals and blueprints for deep, globally shared common agreement. That is, we all agree education, health, and equality have value, but we lack common units for understanding who and who is not contributing value—leaving us to fumble in our own, uncoordinated siloes as we chase the phantoms of impact. In essence, we lack common currencies for our common agreements.

Now we find ourselves at the nexus of the real paradigm of Blockchain, allowing us to fuse economics with inherent value by proving the participation of some great human effort, then quantifying the impact of that effort in unforgeable and decentralized ledgers. It allows us to build economic models for tomorrow, that create wholly new markets and economies for and around each of the richest of human endeavors.

In late 2017 at the height of the Bitcoin bubble, without individual coordination, planning, or the help of institutions, almost $1 trillion was infused into blockchain markets. This is remarkable, and the revolution has only just begun. When you realize that Blockchain is in a similar stage of development as the internet pre-AOL, you will see a glimpse of the global transformation to come.

Only twice in the information age have we had such a paradigm shift in global infrastructure reform—the computer and the internet. While the computer taught us how to store and process data, the Internet built off that ability and furthered the conversation by teaching us how to transfer that information. Blockchain takes another massive step forward—it builds off the internet, adding to the story of information storage and transfer—but, it teaches us a new, priceless and not yet understood skill: how to transfer value.

This third wave kicked off with a rough start—as happens with the birth of new technologies and their corresponding liberties. Blockchain has, thus far, been totally unregulated. Many, doubtless, have taken advantage. A young child, stretching their arms for the first couple times might knock over a cookie jar or two. Eventually, however, they learn to use their faculties—for evil or for good. As such, while it’s wise to be skeptical at this phase in blockchain’s evolution, it’s important not to be blind to its remarkable implications in a post-regulated world, so that we may wield its faculties like a surgeon’s scalpel—not for evil or snake-oil sales, but for the creation of more good, for the flourishing of commonwealth.

But what of the volatility in blockchain markets? People agree Bitcoin has value, but they don’t understand why they are in agreement, and so cryptomarkets fluctuate violently.  Stable blockchain economies will require new symbolic gold standards that clearly articulate why someone would agree to support each market, to anchor common agreement with stability. The more globally shared these new value standards, the better.

Is education more valuable than gold? What about healthcare or nutrition or clean water?

We set out in 2018 to prove a hypothesis—we believe that if you back a cryptocurrency economy with a globally agreed upon inherent value like education, you can solve for volatility and stabilize a mature long lasting cryptomarket that awards everyone who adds value to that market in a decentralized way without the friction of individual partnerships.

What if education was a new gold standard?

And what if this new Learning Economy had protocols to award everyone who is helping to steward the growth of global education?

Education is a mountain. Everyone takes a different path to the top. Blockchain allows us to measure all of those unique learning pathways, online and in classrooms, into immutable blockchain Learning Ledgers.

By quantifying the true value of education, a whole economy can be built around it to pay students to learn, educators to create substantive courses, and stewards to help the Learning Economy grow. It was designed to provide a decentralized way for everyone adding value to global education to coordinate around the commonwealth without the friction of individual partnerships. Imagine the same for healthcare, nutrition, and our environment?

Imagine a world where we can pay refugees to learn languages as they find themselves in foreign lands, a world where we can pay those laid off by the tide of automation to retrain themselves for the new economy, a world where we can pay the next generation to prepare themselves for the unsolved problems of tomorrow.

Imagine new commonwealth economies that alleviate the global burdens of poverty, disease, hunger, inequality, ignorance, toxic water, and joblessness. Commonwealths that orbit inherent values, upheld by immutable blockchain protocols that reward anyone in the ecosystem stewarding the economy—whether that means feeding the hungry, providing aid for the global poor, delivering mosquito nets in malaria-ridden areas, or developing transformative technologies that can provide a Harvard-class education to anyone in the world willing to learn.

These worlds are not out of reach—we are only now opening our eyes to the horizons of blockchain, decentralized coordination, and new gold standards. Even though coordination is the last of the seventeen sustainable development goals, when solved, its tide will lift for the rest—a much-needed rocket fuel for global prosperity.

“Let us raise a standard to which the wise and the honest can repair.”  —George Washington
The views presented in this article are the author’s own and do not necessarily represent the views of any other organization.