Machine meritocracy is here. In this article, the authors elaborate on questions of inclusivity, fairness, and governance. Will we survive as we are or is there a need for a new Magna Carta?
We stand at a watershed moment for society’s vast, unknown digital future. A powerful technology, artificial intelligence (AI), has emerged from its own ashes, thanks largely to advances in neural networks modelled loosely on the human brain. AI can find patterns in massive unstructured data sets, improve performance as more data become available, identify objects quickly and accurately, and, make ever more and better recommendations and decision-making, while minimising interference from complicated, political humans. This raises major questions about the degree of human choice and inclusion for the decades to come. How will humans, across all levels of power and income, be engaged and represented? How will we govern this brave new world of machine meritocracy?
To answer this question, we need to travel back 800 years: January 1215 and King John of England, having just returned from France, now faced angry barons who wished to end his unpopular vis et voluntas (“force and will”) rule over the realm. In an effort to appease them, the king and the Archbishop of Canterbury brought 25 rebellious barons together to negotiate a “Charter of Liberties” that would enshrine a body of rights to serve as a check on the king’s discretionary power. By June they had an agreement that provided greater transparency and representation in royal decision-making, limits on taxes and feudal payments, and even some rights for serfs. The famous “Magna Carta” was an imperfect document, teeming with special-interest provisions, but today we tend to regard the Carta as a watershed moment in humanity’s advancement toward an equitable relationship between power and those subject to it. It set the stage eventually for the Enlightenment, the Renaissance and democracy.
It is that balance between the ever-increasing power of the new potentate – the intelligent machine – and the power of human beings that is at stake. In a world in which machines will create ever more value, produce more of our everyday products with reducing human control over designs and decisions. Existing work and life patterns are changing forever. Our creation is running circles around us, faster than we can count the laps.
This goes well beyond jobs and economics: in every area of life machines are starting to make decisions for us without our conscious involvement. Machines recognise our past patterns and those of allegedly similar people across the world. We receive news that shapes our opinions, outlooks and actions based on inclinations we expressed in past actions, or the actions of others in our bubbles. While driving our cars, we share our behavioural patterns with automakers and insurance companies so we can take advantage of navigation and increasingly autonomous vehicle technology, which in return provides us new conveniences and safer transportation. We enjoy richer, customised entertainment and video games, the makers of which know our socioeconomic profiles, our movement patterns and our cognitive and visual preferences to determine pricing sensitivity.
About the Author
Dr. Olaf Groth, Ph.D. is CEO of Cambrian.ai, a network of advisers on the global innovation economy for executives and investors. He serves as Professor of Strategy, Innovation & Economics at Hult International Business School, Visiting Scholar at UC Berkeley’s Roundtable on the International Economy, and the Global Expert Network member at the World Economic Forum.
Dr. Mark Nitzberg, Ph.D. is Executive Director of the Center for Human-Compatible AI at the University of California at Berkeley. He also serves as Principal & Chief Scientist at Cambrian.ai, as well as advisor to a number of startups, leveraging his combined experience as a globally networked computer scientist and serial social entrepreneur.
Dr. Mark Esposito, Ph.D., is a socio-economic strategist and bestselling author, researching MegaTrends, Business Model Innovations and Competitiveness. He works at the interface between Business, Technology and Government and co-founded Nexus FrontierTech, an Artificial Intelligence Studio. He holds appointments as Professor of Business and Economics at Hult International Business School and Grenoble Ecole de Management and he is equally a faculty member at Harvard University since 2011. Mark is an affiliated faculty of the Microeconomics of Competitiveness (MoC) network at Harvard Business School’s Institute for Strategy and Competitiveness and is currently co-leader of the network’s Institutes Council.