Establishing global leadership through a bold AI policy and plan is critical for the economic growth and stability of our society
According to the headlines, the Age of Artificial Intelligence is dark and dystopian — with self-aware, killer robots coming for us all. Such storylines make for blockbuster movies, but they lack a true understanding of AI, how quickly it’s developing and what technological barriers exist.
The Age of AI is coming, and fast, and there is plenty to be concerned about. But the Terminator isn’t one of them.
The real threat? Most of the world, including the United States, is unprepared to reap many of the economic and societal benefits offered by AI or mitigate the inevitable risks. Getting there will take decades. Yet AI applications are advancing faster than our policies or institutions at a time in which science and technology are being under-funded, undersupported and even challenged.
It’s a national emergency in the making.
The United States needs a human-centered AI framework that guides a national policy and plan — a framework anchored by our shared American values of equality, opportunity and agency: AI should improve the human condition.
We need bold leadership, a national vision and a values-driven framework for international standards, policies and principles. This requires an unprecedented collaboration and commitment of international, federal, state and local governments, as well as academia, nonprofits and corporations.
Early efforts from Washington — a commitment to invest nearly $1 billion in R&D across multiple agencies and programs in 2020; the AI Executive Order from February, which called for an updated research and development strategy for federal agencies, an open approach to data and the development of international standards; and bills to make modest investments in AI research — are encouraging, but not nearly enough.
If guided properly, the Age of AI could usher in an era of productivity and prosperity for all. PWC estimates AI will deliver $15.7 trillion to the global economy by 2030. However, if we don’t harness it responsibly and share the gains equitably, it will lead to greater concentrations of wealth and power for the elite few who usher in this new age — and poverty, powerlessness and a lost sense of purpose for the global majority.
The potential financial advantages of AI are so great, and the chasm between AI haves and have-nots so deep, that the global economic balance as we know it could be rocked by a series of catastrophic tectonic shifts.
Competition will become fiercer as the stakes get higher. Developed countries might have no choice but to push automation to capture higher productivity. Leading AI countries could capture an additional 20%-25% in net economic benefits, while developing countries might see only 5% to 15%, according to McKinsey. Falling behind will have disastrous effects on a nation’s prospects. Even within regions prescient enough to invest in AI, the resulting economic and class divisions could lead to dangerous political and societal clashes.
AI has the ability to be a force multiplier of our very best — and very worst — intentions. It can help us address our most vexing challenges: managing natural resources; mitigating climate change; detecting and treating disease earlier and more effectively; caring for the elderly; increasing the food supply for a growing global population; physical and cybersecurity; efficient transportation and infrastructure; and much more. But it is also displacing jobs and possibly entire industries; exacerbating ethnic and gender bias in criminal justice, finance and employment; promoting propaganda and deep fakes; and increasing threats to privacy and data security.
We’ve seen the damage that can happen when technology is adopted faster than the policies that govern it, and without forethought about ethics or negative impacts. The best way to minimize these issues is for the people who develop AI to reflect the population that will be affected by it.
This new framework must prioritize inclusivity and interdisciplinary collaboration.
Our future depends on the ability of social- and computer scientists to work side-by-side with people from multiple backgrounds — a significant shift from today’s computer science-centric model. The creators of AI must seek the insights, experiences and concerns of people across ethnicities, genders, cultures and socio-economic groups, as well as those from other fields, such as economics, law, medicine, philosophy, history, sociology, communications, human-computer-interaction, psychology, and Science and Technology Studies (STS). This collaboration should run throughout an application’s lifecycle — from the earliest stages of inception through to market introduction and as its usage scales.
To execute a human-centered national AI strategy, we propose that the US government build a new AI ecosystem across education, research and entrepreneurship, with an investment of at least $120 billion over ten years.
1: Support public research to pursue the next generation of AI breakthroughs, with an emphasis on interdisciplinary research.
Budget: $7 billion/ year.
Many of the world’s most impactful technologies — broadband; the internet; sequencing the human genome — have resulted from partnerships between government and academia. We should establish national and regional research hubs in partnership with leading universities and emphasize cross-disciplinary research and diverse teams.
Training AI requires vast stores of data and robust computing power, a major advantage to giant corporations whose incentive structures promote “click-through” rates over benefits to society. Collaboration between public organizations would ensure breakthroughs are developed in the interest of society and launching a National Research Cloud would provide high value data and high-performance computing for public-interest research.
2: Invest in education, with an emphasis on inclusion.
Budget: $3 billion (double the current annual federal K-12 STEM spend)
As many as 30% of jobs could be automated by the mid 2030s, according to PWC, yet employment for software developers is expected to grow 24% between 2016 and 2026 — not including machine learning or robotics. In 2016, fewer than 15% of tech positions were held by black or hispanic people. Women comprise just 25% of computing roles and only 12% of machine learning researchers. This must change in order to mitigate bias and build applications that benefit more than a privileged few.
The US needs to educate a more diverse future workforce in science, technology, engineering and math (STEM), including artificial intelligence and computer science, as well as support research and programs to address job displacement and reskilling.
3: Spur innovation and support entrepreneurs.
Entrepreneurship is the heart of our economy. The Small Business & Entrepreneurship Council estimates firms with fewer than 100 employees comprise 98% of US businesses. They drive innovation and competition, create new jobs and challenge monopolistic organizations. We should provide early-stage support for emerging technologies through grants, investment and technical resources, with an emphasis on agriculture, manufacturing, healthcare, sustainability and clean energy.
4: Implement clear, actionable international standards and guidelines for the ethical use of AI
Partner with foreign governments, companies, and civil society organizations to concretely implement global AI principles, such as those developed by the OECD.
Leading the world in the development of a human-centered AI framework is central to our ideals as a nation, and critical for the future economic growth and stability of our society. AI's technical development must co-evolve with policies that ensure its responsible use. AI is advancing rapidly, but we still have time to get it right — if we act now.