Frank Levy an economist and Professor at MIT and Harvard, who work’s on technology’s impact on jobs and living standards, has written to assay the sensationalized fears of the overhyped study by Frey and Osborne. Levy indicates:
- The General Proposition – Computers will be subsuming an increasing share of current occupations – is unassailable.
- The Paper (Frey and Osborne study) is a set of guesses with lots of padding to increase the appearance of “scientific precision.”
- The authors’ understanding of computer technology appears to be average for economists (= poor for computer scientists). By my personal guess, they are overestimating what current technology can do.
Researchers at the OECD analyzed the Frey and Osborne study and conducted their own research on tasks and jobs and concluded that: “automation was unlikely to destroy large numbers of jobs.”
I have also been quite critical of the Frey and Osborne study based on my understanding of technological advances, which they claim to be way more ahead than it is:
We argue that it is largely already technologically possible to automate almost any task, provided that sufficient amounts of data are gathered for pattern recognition.
With the exception of three bottlenecks, namely:
“Perception and manipulation.”
Frey and Osborne divided the tasks involved in jobs along two dimensions: cognitive vs. manual and non-routine vs. routine. They then identified three aspects (bottlenecks) of a job making it less likely that a computer would be able to replicate the tasks of that job: First, “perception and manipulation” in unpredictable tasks such as handling emergencies, performing medical treatment, and the like. Second, “creative intelligence” such as cooking, drawing, or any other task involving creative values relying on novel combinations of inspiration; Third, “social intelligence”, or the real-time recognition of human emotion.
Race with the machines
Now a new research paper, released in July 2016, by researchers at the Centre for European Economic Research has indicated that technology has in fact had the opposite impact and is a net creator of jobs not destroyer (at least in 27 European countries – and I suspect the same is true for other regions).
The paper, Racing With or Against the Machine? Evidence from Europe by authors Terry Gregory, Anna Salomons, and Ulrich Zierahn (Gregory and Zierahn were also two of the OECD paper authors) looked at the impact of routine replacing technology on jobs and concluded:
Overall, we find that the net effect of routine-replacing technological change (RRTC ) on labor demand has been positive. In particular, our baseline estimates indicate that RRTC has increased labor demand by up to 11.6 million jobs across Europe – a non-negligible effect when compared to a total employment growth of 23 million jobs across these countries over the period considered. Importantly, this does not result from the absence of significant replacement of labor by capital. To the contrary, by performing a decomposition rooted in our theoretical model, we show that RRTC has in fact decreased labor demand by 9.6 million jobs as capital replaces labor in production. However, this has been overcompensated by product demand and spillover effects which have together increased labor demand by some 21 million jobs. As such, fears of technological change destroying jobs may be overstated: at least for European countries over the period considered, we can conclude that labor has been racing with rather than against the machine in spite of these substitution effects.
My research of companies using robots has also categorically shown, through factual evidence, that those companies have created significantly more jobs than have been lost due to technological change. Similarly a detailed analysis prepared for the European Commission Director General of Communications Networks, Content & Technology by Fraunhofer about the impact of robotic systems on employment in the EU found that:
European manufacturing companies do not generally substitute human workforce capital by capital investments in robot technology. On the contrary, it seems that the robots’ positive effects on productivity and total sales are a leverage to stimulate employment growth.
So if robots are not job killers what is the real problem?
We need to fill the skills gap
I have argued before that we have a skills problem. Jobs all over the world are not being filled because of lack of skilled personnel to fill them.
New and emerging technologies both excite and worry. Robotics and Artificial Intelligence (AI) is certainly a minefield for both exuberance and fears.
By definition, there is a knowledge and skills gap during the emerging stages of any new technology, Robotics and AI is no exception: researchers and engineers are still learning about these technologies and their applications. But, in the meantime, hope, fears and hype naturally and irresistibly fill this vacuum of information.
Depending on whom you ask Robots and AI is predicted to help solve the world’s problems. Or by building this devil, these technologies may scorch the earth and fulfill a prophecy of Armageddon.
On the other side, especially with respect to AI, what it will most likely do – if and only if adopted by major corporations and governments — is foster technological and institutional betterment at a frenetic pace through improved health care, solving climate problems, helping those with sight problems, helping to get much needed aid spread more equitably.
We need education and training fitted to a different labour market, with more focus on creativity, flexibility and social skills. We need more Moonshots from Governments and Industry as so well described by Mariana Mazzucato in her book the Entrepreneurial State: Debunking Public vs. Private Sector.
Machines are there to augment human intelligence and ingenuity, to improve our environment and workplace, we need to stop fearing the machines and learn how to better integrate them into our processes, destroy the fears and improve productivity. We are not going to stop technological progress, if we embrace it we are better prepared to gain from it.
Goldman Sachs (“GS”) has released a series of research reports in 2016 centered on The Factory of the Future.
The series which they call ‘Profiles in Innovation’ examines six technologies GS believe is driving transition, from “Cobots” to 3D printing to Virtual and Augmented Reality to the Internet of Things, and how these technologies could yield more than US$500 billion of cost savings.
As part of the GS team’s investigations they hosted a Factory of the Future field-trip for investors at Automatica trade fair in Munich, Germany on June 25, 2016. They subsequently provided a synopsis of their key observations.
Here are the top takeaways from GS’s field trip to Automatica related to Robots.
Universal Robots (“UR”)
- Universal Robots’ cobots have a payback of 6 months and overall installation costs at <2x cost of robots vs. >3x for traditional robots. Cheapest UR cobot costs just €20k.
- Universal Robots believes its sales network, brand and open-source strategy will be important to lock-in and outgrow the cobot market.
- Amidst its own impressive growth, Universal Robots is preparing for tougher competition.
Universal Robots, Teradyne’s market leading collaborative robots business, hosted a booth tour. Key takeaways were:
- With the cobot market growing >50% pa in recent years, Teradyne (owner of UR) is targeting $90 million to $100 million in revenues for Universal Robots for 2016. UR believes this fast growth is unlikely to hit capacity constraints as its current Denmark-based manufacturing set-up can generate $500 million in revenues without the need for significant factory cap expenditure.
- The customer base for Universal Robots consists largely of SME enterprises in a wide range of end markets. As a result, its method-to-market and ease-of-use is key to achieving rapid organic growth. It uses distributors (which pick up servicing margin in return for broad dissemination) and a user-friendly set-up, eliminating the need for third party engineers to program the robot.
- Universal Robots believes that its technology is 2-3 years ahead of competitors (15 other booths at the fair were using UR cobots), however it is aware that the competition is increasing significantly. Leveraging Teradyne’s balance sheet they believe acting quickly and the use of their open-source platform (meaning that a wide range of components are easy to develop, described as an “App store” approach) is key to dominating this quickly evolving market.
- Cobot competition is picking up as Yaskawa entered the race and Fiat Chrysler’s Comau are pioneering solutions to concerns about speed.
- Yaskawa demonstrated five of its new product launches, underpinning our growth expectations and mix improvement as it increases appeal in general industry.
Yaskawa hosted a booth tour and interview with its EU operations management. The company exhibited several new products:
- 10 kg payload collaborative robots
- 7-axis robots with the newest spot welding gun and smaller, low pay-load robots ideal for general industry.
- Motologix software (bridging machine communication between controllers and PLCs (programmable logic controller) – based on VIPA (acquired German company PLC technology).
Goldman Sachs, who said they came away with a great deal of confidence in Yaskawa’s product mix, also offered the following key takeaways:
- Looking at collaborative robots specifically, GS believe the company has strong positioning as one of the ”Big Four” robotics company. They believe pricing is reasonable at €38,000 for 10kg weight handling, with sensors implemented in all axis and easy teaching system. Given that many start-up companies were introducing cobots with, in the GS teams opinion, inferior quality and yet similar pricing (€20-40,000 per unit), GS felt Yaskawa is well positioned to capture the growth of the cobot market.
- Yaskawa sold 25,000 robots in 2015; which GS estimate that Yaskawa has circa 10% market share (note these will be mainly premium robots), bringing Yaskawa’s total installed base to 350k.
Other general observations by the Goldman Sachs team
- Despite the absence of a major global robotics player, the US (where robotics is growing double digit) is still at the forefront in automation, by developing the embedded technologies required.
- Beware of the buzzwords: Most notably, AI and cloud robotics. Association for Advancing Automation thinks it might take decades to get commercializable AI products.
- Machine vision is a >$2 billion market, despite in a current downturn, according to the Association for Advancing Automation.
- Flexibility and efficiency are crucial in leading autos factories, as BMW produces a car in 44 hours with no two likely to be the same each day.
- The average age of workers in BMW’s Welt factory is rising (43 vs. 40 a few years ago) as new technologies, such as exoskeletons, are increasing the longevity of employees.
Check out Goldman Sachs briefings and video for additional information.
New technologies, such as drones, are giving humanity new capabilities and techniques to simplify otherwise complex situations and improve lives by doing so.
One of the best examples of drones overcoming complexity, by leapfrogging infrastructure constraints, to do good is the RedLine cargo drones and drone ports initiative led by Jonathan Legard and designed by famed architect Lord Norman Foster.
Foster who is credited with ‘inventing’ the modern airport and the world’s biggest airport, plus the world’s first purpose-built commercial spaceport for Virgin Galactic in New Mexico and designed Lunar building studies, which would be built by robots, in conjunction with the European Space Agency, as well as creating some of the world’s most iconic building designs has partnered with Legard’s RedLine Drones and has built the first prototype Drone Port which he says will have a very broad social agenda.
Very complex supply chain challenges
Lagard has identified Rwanda to be the first destination on the African continent to build the Drone Port designed by The Norman Foster Foundation, which was able to harness the creativity of students and professors from five universities around the world at institutions including MIT, ETH Zurich and others from industry such as LafargeHolcim Foundation for Sustainable Construction.
The majority of roads in Rwanda are mere dirt lanes with large potholes and mud tracks. Trucks, 4 x 4 vehicles and cars frequently break down and the estimated time of arrival of cargo is often determined in days, rather than hours. With its inadequate road and rail infrastructure, wide-open spaces, favorable regulatory bodies and relatively quiet skies Rwanda is highly suited to operating cargo drones.
Norman Foster has expressed his belief that RedLine drones can reduce transport constraints and create better links between regions and among remote communities and deliver consignments, such as critical medical supplies, in one twelfth of the time of a Land Rover.
Small helicopter-type drones with little payloads and limited ranges are useful for photography, surveillance and perhaps so-called ‘last-mile’ (final) delivery in highly developed places with good infrastructure. But they would be ineffective in such a complex infrastructure as Rwanda.
RedLine’s fleet of fixed-wing drones have a 10 feet (3 meter) wingspan, 22 lbs (10 kilogram) payload and 31 miles (50 kilometer) range. These drones will transport emergency cargo; primarily blood to treat malaria of which 450,000 people die every year in Africa, sickle cell disease, which results in more than 100,00 deaths each year and blood for transfusions for mothers during childbirth – more than 60,000 mothers die each year due to bleeding and lack of access to blood.
Once the initial network of RedLine drones is operational, the plan is to introduce the BlueLine fleet of larger drones with a 20 feet (6 meters) wingspan, 220 lbs (100 kilogram) payload and 62 miles (100 kilometer) range by 2025.
The idea is that in the long term BlueLine will help subsidize RedLine’s humanitarian activities by carrying commercial cargo for fee-paying clients.
DronePort more than a hangar for drones
With a rapidly growing population Africa is facing exponential growth that is set to double to 2.2 billion people across the continent by the year 2050. In particular Rwanda also faces the prospect of up to 70 percent youth unemployment.
With this in mind the architects have designed the DronePorts with a unique structure so that minimum products are imported and the maximum materials and building construction is done locally leading to short and long-term sustainable development and employment in the local community.
In addition for a place to operate, build and repair the drones, Foster envisions DronePorts will become a catalyst for other industries to develop and prosper, such as e-commerce, health care and education facilities, he hopes the ports will have a strong civic presence, based on sharing and multiple uses where marketplace and community centers will flourish.
A full-scale prototype of the DronePorts was built in May 2016 at the 15th International Architecture Biennale. The buildings construction, with bricks made from stabilized earth, a reliable, affordable and environmentally friendly building material, which does not require intensive use of fuel, was filmed to serve as a model for replication by local communities in emerging economies.
The Norman Foster Foundation is working on creating a ‘SolarBrick’, which could be incorporated into the structure of the droneport vaults. The ‘SolarBrick’ will have solar cells on its outer surface, charging a long-life battery and then powering a LED lamp on the inner surface.
The innovative design of the DronePorts has been designed with the goal of ensuring the drone is capable of delivering cargo and urgent medical supplies quickly and cheaply top overcome the limitations caused by poor infrastructure.
Foster and Lagard both believe Africa will be the first continent to adopt flying robots for cargo at a massive scale.
It’s not technologies that change the world it’s the people who implement and use them.
Additional links to articles, photos and videos
Founded in Spain in 1861 in Penedès, the main district of Catalonia, Freixenet S.A. currently owns 18 wineries across three continents and is one of the best-known Spanish wine brands. The 155 years old family owned business has annual sales exceeding Euro 500 million (US$ 560 million) and produces over 200 million bottles of sparkling wine each year.
The sparkling wine is known as “cava” due to the fact that much of the production fermentation process is in a network of several miles of underground caves or cellars. To be branded cava, sparkling wine must be produced in the ‘champenoise traditional method’, in the past cava was referred to as “Spanish champagne”, however this branding is no longer permitted under European Union law. Nevertheless the method of production for cava and Champagne are pretty much the same in which wine is fermented twice and sugar added to make it bubbly.
Sparkling wine is currently the key growth area in the beers, wine and spirits category. This growth has caused some challenges for Freixenet to increase production capacity to the same degree as an increase in the success of the brand and its products. The challenges are compounded by the traditional methods of production which require that processes are maintained, in fact according to Josep Palau, Head of Production at Freixenet:
What has not changed at all is our traditional elaboration process, which still includes each and every one of the stages as they were undertaken 50 years ago. We collect the grapes, make the base wines, bottle them, ferment them, then the crianza process begins, disgorging, etc. But what we have done continuously is make these stages more technical and automated in order to adapt ourselves to an increase in demand.
Those changes in production also depend on the particular cava being produced; the process is either done by hand (for the very top cuvees), or increasingly by automation. For example the company now uses pneumatic presses with a soft membrane that creates a pressure similar to traditional foot treading for pressing the grapes.
Once the grapes are pressed the ‘must’ from which the base wines are made is mixed in large vats by adding sugar, yeast and clarifiers, this then undergoes a bottling process and then the wines are taken to the cellars for fermentation. The fermentation involves the use of computerized automation that slowly rotate the bottles to help the build up of the carbon dioxide gas needed for cava’s characteristic bubbles. Depending on the product, this may range from a minimum of nine months to three years or more in higher quality wines.
Of Freixenet’s 1700 employees worldwide approximately 350 are employed at their main production facility. According to Josep Palau a large number of employees are involved in heavy manual tasks of moving the bottles around.
Once the base wines are bottled, the bottles have to be stored in cellars and this requires a great deal of internal logistics.
The cellar process, whether it is positioning the bottles or retrieving them a year later for the clarifying process before disgorging, involves a lot of internal movement and labor.
To help overcome many of the handling, maneuvering and bottling problems Freixenet have installed 36 industrial robots from Fanuc. With the help of Fanuc’s robots production capability has increased substantially. Josep Palau says:
Now an operator can move 500 bottles with each action rather than the two bottles before. The disadvantage before was that, as well as continuing to need somebody to intervene manually, the process also took up a lot of space in our cellars.
The next major innovation was automating the stacking process, or placing the bottles in the cellars, which had previously been done manually until Freixenet’s technicians and a local engineer came up with and implemented a robotic system that allowed the job to be done more efficiently. Mr. Palau believes this automation was the most significant milestone in improving productivity and reducing waste:
This was probably one of the most important innovations that was introduced. Later, and in the aim of being able to manage a great number of bottles, a new bottling process was created, which was almost completely automated and was fully robotized during the end stage. The bottles leave the production line via an automated transport system and arrive directly to the cellars, where an automatic robot system positions them in place for the crianza stage.
By automating this process, work was greatly simplified and our ability to handle this removal step increased enormously, thereby allowing us to handle growth.
In addition to increasing productivity by more than 32 per cent since the introduction of the robots and securing jobs, Freixenet have also discovered environmental benefits from the new technology for bottling and handling. The automation has resulted in a reduction of 25 per cent of the organic pollution load, chemical oxygen demand (COD) of wastewater per unit produced between 2012-2014, and glass waste has been reduced by 7 per cent.
In Spain, one of the key dates on the calendar in the run-up to Christmas is the first broadcast of the Freixenet TV advert. A tradition established in 1978, which has been graced through the years by celebrities such as Demi Moore, Pierce Brosnan, Penélope Cruz, Kim Basinger, Sharon Stone, Antonio Banderas, Paul Newman, Josep Carreras, Plácido Domingo, and many more. The celebrities of the 2012 campaign were two of Freixenet’s production Fanuc robots saluting with 2 glasses of cava. Cheers!
The existence of new drone regulations hasn’t dampened the appetite of prospective drone users for commercial purposes. There’s a ground swell of commercial users looking to get permission for drone use in areas as diverse as retail deliveries, agriculture crop spraying, real-estate sales, commercial photography and filmmaking, search and rescue operations, and oil spill monitoring and an abundance of other sectors.
Governments’ approval is seen as a first step in unleashing a potentially multibillion dollar industry that so far has been largely limited to military and law enforcement applications and more recently monitoring of pipelines along Alaska’s northern shore and energy lines of the National Grid in the UK.
As regulations are clarified and ratified one industry that has seen early adoption of drones is the Insurance sector. In a recent report by PwC, the global audit and consulting firm estimates:
The addressable market of drone powered solutions in the insurance industry at US$ 6.8 billion.
There are three areas where drone operations can enhance an insurer’s procedures: risk monitoring, risk assessment and claims management
After a natural catastrophe, a drone could reach a remote scene much faster than a claims adjuster.
The largest insurance loss event globally in 2015, of both natural and man-made disasters, was the two explosions at the Port of Tianjin in China, which triggered property claims of between US$ 2.5 to US$ 3.5 billion according to reinsurance company Swiss Re. This was also the largest man-made insured loss event in Asia ever recorded.
The Tianjin explosions have presented insurers with a number of challenges, not least lack of access to the affected area to assess the full extent of damage and resulting insurance claims.
According to a report from insurer Swiss Re:
Drone and satellite imagery have helped loss assessment (at the Port of Tianjin). Drones were sent in to take pictures of the disaster site immediately after the explosions.
These images were compared with satellite images of the site taken prior to the event.
The comparison provided a view of the extent of destruction, and also of the high number of vehicles and containers on the site at the time of the explosion. Initial loss assessments have been based on this information.
This would not have been possible without drones because of the 3 kilometers (1.86 miles) radius exclusion zone enforced at the site. The alternative would have been to wait until the exclusion zone was relaxed and use manned aircraft to take pictures after the event from high altitude, which would have been more expensive and may not have produced the same quality images.
Drones have the advantage of being small, low-cost and able to closely survey and photograph large areas more efficiently. Damaged areas such as Tianjin may not be visible by satellites and manned aircraft, for example due to dust cover, or may be inaccessible for first-hand human inspection due to contamination or transport outages after a disaster event.
Another example of where drones are now being deployed to areas unreachable by claims adjusters is in a flood zone. In December 2015, drones were used to take pictures over Cumbria in the UK after large areas were flooded due to Storm Desmond. The images allowed for better response planning, and loss adjusters used them to identify the worst- affected areas and properties for which claims were reported, which in turn facilitated initial claims reserving.
Significant cost savings
AXA Group, the world’s largest insurer with revenues approaching US$ 100 billion and a recently released strategy to become a leader in digital and technological insurance is carrying out trials of drones in France and Belgium. The company says:
Drones fly over inaccessible damaged areas to gather images or videos, which are immediately sent to remote claims adjusters so they can update clients on the loss, trigger communication and potentially advance payments to clients. Using drones can therefore increase trust and transparency and improve the customer experience.
Besides the speed of deploying resources and payments to those insured, the cost savings to insurers could be significant. No longer must underwriters travel in person to inspect the exterior of a building or property. Details of a risk could be validated without incurring travel costs or costs to make in-person inspections.
After a claim is filed, an adjuster could dispatch a drone to investigate the claim. Instead of climbing a ladder to inspect an icy patch of a damaged roof, a claims adjuster could dispatch a drone to conduct the inspection.
Drones can also survey objects from the side rather than just from above, and can facilitate 3D reconstruction of an environment using stereoscopic cameras. These are valuable inputs for improved damage assessment.
Drones could certainly save insurance carriers the costs associated with claims’ adjusters’ worker’s compensation claims.
Drones provide underwriters and claims personnel with a safe, cost-effective alternative to physical inspections.
There are many obstacles still to overcome, privacy issues, data protection, nuisance, physical or bodily harm. These obstacles present a new opportunity to insurers – as individuals and companies obtain Certificate of Authority to fly drones, to become drone pilots, these individuals and companies will also require insurance coverage for their drone activities. A study commissioned by the European Commission found that drone operations do carry the potential to generate liability claims requiring lengthy and complex legal proceedings.
While insurance company use of, and indeed insurance coverage for, commercial drones is “up in the air,” there’s no question that the drone market is a key growth area.
 PwC Global, Clarity from Above May 2016 (https://www.pwc.pl/pl/pdf/clarity-from-above-pwc.pdf) Last accessed July 5th, 2016
 Swiss Re, Sigma Number 1/2016 “Natural catastrophes and man-made disasters in 2015”
 “Drones will transform loss adjusting”, Insurance Day, January 2nd, 2016 (https://www.insuranceday.com/news_analysis/special_reports/drones-will-transform-loss-adjusting.htm) last accessed July 5th, 2016
Axa Drones Start-in 2016 (https://www.axa.com/en/newsroom/news/start-in-2016. Last accessed July 5th, 2016
 Steer Davies Gleave for European Commission, 2014. Study on the Third-Party Liability and Insurance Requirements of Remotely Piloted Aircraft Systems (RPAS) (https://www.eurocontrol.int/sites/default/files/ec_rpas_final_report_nov14_steer_davies.pdf) Last accessed July 5th, 2016
Picture credit Brian Moore Draws Creative Commons
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).
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.
 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.