Robotics, Artificial intelligence (AI) has held a place in our imaginations for the better part of a century. Recently, these futuristic ideas have become a reality, earning artificial intelligence a constant place in the spotlight of the business world. Advancements in artificial intelligence have enabled companies to act on robust data sets, giving executives the ability to make data-driven decisions at a moment’s notice.
Accelerating Artificial Intelligence capabilities will enable automation of some tasks that have long required human labor. Rather than relying on closely-tailored rules explicitly crafted by programmers, modern AI programs can learn from patterns in whatever data they encounter and develop their own rules for how to interpret new information. This means that AI can solve problems and learn with very little human input. In addition, advances in robotics are expanding machines’ abilities to interact with and shape the physical world. Combined, AI and robotics will give rise to smarter machines that can perform more sophisticated functions than ever before and erode some of the advantages that humans have exercised. This will permit automation of many tasks now performed by human workers and could change the shape of the labor market and human activity.
Today’s AI uses machine learning in which you give it examples of previous games and let it learn from those examples. The computer is taught what to learn and how to learn and makes its own decisions. What’s more, the new AIs are modeling the human mind itself using techniques similar to our learning processes. Before, it could take millions of lines of computer code to perform tasks such as handwriting recognition. Now it can be done in hundreds of lines. What is required is a large number of examples so that the computer can teach itself.
The new programming techniques use neural networks — which are modeled on the human brain, in which information is processed in layers and the connections between these layers are strengthened based on what is learned. This is called deep learning because of the increasing numbers of layers of information that are processed by increasingly faster computers. These are enabling computers to recognize images, voice, and text — and to do human-like things.
Humans still maintain a comparative advantage over AI and robotics in many areas. While AI detects patterns and creates predictions, it still cannot replicate social or general intelligence, creativity, or human judgment. Of course, many of the occupations that use these types of skills are high-skilled occupations, and likely require higher levels of education. Further, given the current dexterity limits of the robotics that would be needed to implement mass AI-driven automation, occupations that require manual dexterity will also likely remain in demand in the near term. Additionally, technology will only accelerate our capacity to pursue diverse interests. The Internet has already democratized information, allowing many to become experts in fields in which they have no formal education or training. The future of technology may allow for each of us to become masters in many fields, expanding the abilities of our bodies and our minds.
Technological change in general will shape the distribution of gains in coming years depends on non-technical factors including aspects of both the broader economy and policy institutions. It could yield greater inequality, particularly in its potential to disrupt labor markets. As the development of technology substitutes for labor across the entire economy, the net displacement of workers by robotics, AI, cyber systems, additive manufacturing might exacerbate the gap between returns to capital and returns to labor. On the other hand, it is also possible that the displacement of workers by technology will, in aggregate, result in a net increase in safe and rewarding jobs.
We will continue to experience the overlapping revolutions of genetics, nanotechnology, and AI, robotics simultaneously as each one of these technologies matures. These and other technologies will likely converge and impact our lives in ways difficult to predict, and each technology will have the power to do great good or harm—as is the case with all great technologies. The extent to which we’re able to harness their power to improve lives will depend on the conversations we have and the actions we take today.
Neither technology nor the disruption that comes with it is an exogenous force over which humans have no control. All of us are responsible for guiding its evolution, in the decisions we make on a daily basis as citizens, consumers, and investors. The direction of innovation is not a random shock to the economy but the product of decisions made by firms, governments, and individuals. Economic factors can drive the direction of technological change. Second, there is a role for policy to help amplify the best effects of automation and temper the worst.
To do this, we must develop a comprehensive and globally shared view of how technology is affecting our lives and reshaping our economic, social, cultural, and human environments. There has never been a time of greater promise, or one of greater potential peril. Today’s decision-makers, however, are too often trapped in traditional, linear thinking, or too absorbed by the multiple crises demanding their attention, to think strategically about the forces of disruption and innovation shaping our future.
In the end, it all comes down to people and values. We need to shape a future that works for all of us by putting people first and empowering them. In its most pessimistic, dehumanized form we may indeed have the potential to ‘robotize’ humanity and thus to deprive us of our heart and soul. But as a complement to the best parts of human nature—creativity, empathy, stewardship—it can also lift humanity into a new collective and moral consciousness based on a shared sense of destiny. It is incumbent on us all to make sure the latter prevails.