Home » Artificial Intelligence » Whitehouse Chairman of Economic Advisors – Why We Need More Artificial Intelligence

Whitehouse Chairman of Economic Advisors – Why We Need More Artificial Intelligence

Society is caught between blind faith in technology and resistance to progress, between technological possibilities and fears that it has a negative impact.

Increasingly Artificial Intelligence, the latest buzzword for everything software related, is stirring up much of the fears.

In an interesting paper: Is This Time Different? The Opportunities and Challenges of Artificial Intelligence, Jason Furman, Chairman of President Obama’s Council of Economic Advisers sets out his belief that we need more artificial intelligence but must find a way to prevent the inequality it will inevitably cause. Despite the labor market challenges we may need to navigate, Furman’s bigger worry is that we will not invest enough in AI.

He is more pragmatic than many economists and researchers who have written ‘popular’ books on the subject but calls for more innovation if we are truly to reap the benefits AI and Robotics will bring:

We have had substantial innovation in robotics, AI, and other areas in the last decade. But we will need a much faster pace of innovation in these areas to really move the dial on productivity growth going forward. I do not share Robert Gordon’s (2016) confidently pessimistic predictions or Erik Brynjolfsson and Andrew Mcafee’s (2014) confidently optimistic ones because past productivity growth has been so difficult to predict.

Technology, in other words, is not destiny but it has a price

My worry is not that this time could be different when it comes to AI, but that this time could be the same as what we have experienced over the past several decades. The traditional argument that we do not need to worry about the robots taking our jobs still leaves us with the worry that the only reason we will still have our jobs is because we are willing to do them for lower wages.

Replacing the Current Safety Net with a Universal Basic Income Could Be Counterproductive

Furman says that AI does not create a call for a Universal Basic Income and that the claims for implementing UBI and cancelling other social welfare programs have been greatly overstated:

AI does not call for a completely new paradigm for economic policy—for example, as advocated by proponents of replacing the existing social safety net with a universal basic income (UBI) —but instead reinforces many of the steps we should already be taking to make sure that growth is shared more broadly.

Replacing part or all of that system with a universal cash grant, which would go to all citizens regardless of income, would mean that relatively less of the system was targeted towards those at the bottom—increasing, not decreasing, income inequality.

Instead our goal should be first and foremost to foster the skills, training, job search assistance, and other labor market institutions to make sure people can get into jobs, which would much more directly address the employment issues raised by AI than would UBI.

Past Innovations Have Sometimes Increased Inequality—and the Indications Suggest AI Could Be More of the Same

Relying on the questionable study by Frey and Osborne, Furman says that work by the Council of Economic Advisers, ranked the occupations by wages and found that, according to the Frey and Osbourne analysis, 83 percent of jobs making less than $20 per hour would come under pressure from automation, as compared to 31 percent of jobs making between $20 and $40 per hour and 4 percent of jobs making above $40 per hour (see Figure 1 below).


AI has not had a large impact on employment, at least not yet

Furman says the issue is not that automation will render the vast majority of the population unemployable. Instead, it is that workers will either lack the skills or the ability to successfully match with the good, high paying jobs created by automation.

The concern is not that robots will take human jobs and render humans unemployable. The traditional economic arguments against that are borne out by centuries of experience. Instead, the concern is that the process of turnover, in which workers displaced by technology find new jobs as technology gives rise to new consumer demands and thus new jobs, could lead to sustained periods of time with a large fraction of people not working.

AI has the potential—just like other innovations we have seen in past decades—to contribute to further erosion in both the labor force participation rate and the employment rate. This does not mean that we will necessarily see a dramatically large share of jobs replaced by robots, but even continuing on the past trend of a nearly 0.2-percentage-point annual decline in the labor force participation rate for prime-age men would pose substantial problems for millions of people and for the economy as a whole.

Investment in AI

Mentioning the fact that AI has not had a significant macroeconomic impact yet, Furman indicates that the private sector will be the main engine of progress on AI. Citing references that in 2015 the private sector invested US$ 2.4 billion on AI, as compared to the approximately US$ 200 million invested by the National Science Foundation (NSF).[1]

He says the government’s role should include policies that support research, foster the AI workforce, promote competition, safeguard consumer privacy, and enhance cybersecurity

AI does not call for a completely new paradigm for economic policy

AI is one of many areas of innovation in the U.S. economy right now. At least to date, AI has not had a large impact on the aggregate performance of the macroeconomy or the labor market. But it will likely become more important in the years to come, bringing substantial opportunities— and our first impulse should be to embrace it fully.

He indicates that his biggest worry about AI is that we may not get all the breakthroughs we think we can, and that we need to do more to make sure we can continue to make groundbreaking discoveries that will raise productivity growth, improving the lives of people throughout the world.

However, it is also undeniable that like technological innovations in the past, AI will bring challenges in areas like inequality and employment. As I have tried to make clear throughout my remarks, I do not believe that exogenous technological developments solely determine the future of growth, inequality, or employment. Public policy—including public policies to help workers displaced by technology find new and better jobs and a safety net that is responsive to need and ensures opportunity —has a role to play in ensuring that we are able to fully reap the benefits of AI while also minimizing its potentially disruptive effects on the economy and society. And in the process, such policies could also contribute to increased productivity growth—including advances in AI itself.

What are those policies? Truman indicates we need to develop more “human learning and skills,” increase investments in research and development, this includes Government investment and also “expand and simplify the Research and Experimentation tax credit,” “increase the number of visas—which is currently capped by legislation—to allow more high-skilled workers to come into the country.” “Consolidate existing funding initiatives, help retrain workers in skills for which employers are looking,” and more focused initiatives such as the “DARPA Cyber Grand Challenge.”

The bottom line is that AI managed well, with innovate government support, could offer significant benefits to humanity, but those benefits, including earning capacity, can only be achieved if governments and corporations help people up-skill.

[1] For private funding see https://www.cbinsights.com/blog/artificial-intelligence-funding-trends/#funding. For public funding see http://www.nsf.gov/about/budget/fy2017/pdf/18_fy2017.pdf. According to the NSF, in 2015 there was $194.58 million in funding for the NSF Directorate for Computer and Information Science and Engineering’s Division of Information and Intelligent Systems (IIS), much of which is invested in research on AI. These figures do not include investment by other agencies, including Department of Defense.





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