The Big Reboot, Part 2 – The Economic Impacts of Societal Transitions
Published on September 20, 2019
Rohit Talwar Rohit Talwar – Futurist Speaker
By Rohit Talwar, Steve Wells, Alexandra Whittington, Helena Calle, and April Koury
How can we address a rise in the number of “technologically unemployed” and fund the costs of navigating a turbulent economic transition period?
People and Money
This is the second part of The Big Reboot—a two-part exploration of how we can rethink and experiment with the mechanisms that might help prepare society for technological disruption, automation, and continuing global economic shifts. Part one explored ideas for reskilling society and creating new job opportunities. In this chapter, we explore different ways of supporting the unemployed as they look to transition back into work and at mechanisms for funding all of the ideas explored across both chapters.
In The Big Reboot, Part 1—Rethinking Education and Employment in an Automated Era, we suggested that society cannot possibly know or predict the true impacts of technological disruption on the economy and workforce over the next 20 years. We also argued that our response should not be to sit and hope for innovation and growth to save us. Instead, we believe that now is the time to be thinking the unthinkable, challenging old orthodoxies, and doing experiments that can provide the evidence on which future strategies can be based.
In particular, we want to stimulate new thinking about: 1) preparing the workforce for an uncertain future; 2) creating new jobs and businesses; 3) supporting the unemployed in a fair, dignified, and straightforward manner that enables their search for opportunities; and 4) funding the transitions from this economy to future ones. To help stimulate action, the two chapters build on some of the concepts presented in our recent books Beyond Genuine Stupidity—Ensuring AI Serves Humanity and The Future Reinvented—Reimagining Life, Society, and Business to present a range of experimental ideas. Here we focus on the latter two domains—supporting the unemployed and funding the transition.
Rethinking Unemployment
Even before the potential crisis of persistent technological unemployment is upon us, the battle lines have been drawn between those for and against ideas like Universal Basic Incomes (UBI). We would argue that the debate should be informed by a wide range of policy experiments that reflect views across the entire spectrum of opinions. The key seems to be ensuring that unemployment is not stigmatized. Rather, it should instead be treated as a period where the individual is rebuilding their confidence, acquiring news skills, developing a new business, or serving the community. The discussion and experimentation can then shift to exploring how best to support them to feel like a valued member of society. To that end, here are some of the ideas we have been exploring.
Guaranteed Basics
Universal/Guaranteed Basic Incomes—There will inevitably be employment casualties from the process of automation. The question arises as to the extent to which people will be able to afford the goods and services now being produced by the machines if they no longer have jobs. Many are arguing for provision of a guaranteed UBI across society—that pays a living wage to everyone—at a rate typically higher than unemployment benefit. Countries around the world from Canada and Finland to India and Namibia have been experimenting with different models for how this might work. At the time of writing, the newly elected coalition government of Italy has a manifesto commitment to introduce such a mechanism.
The risk of rising long-term unemployment is a real one, and something will need to be done. Simply ignoring the reality and insisting that people find work won’t solve the problem or feed their dependents. We believe governments could work together to conduct a range of UBI experiments. The aim would be to test different delivery models and payment levels to see the impacts on take-up, funding costs, economic activity, the shadow economy, social wellbeing, crime, domestic violence, and mental health. There are already strongly polarized political views on such an option. However, doing the experiments is not committing to the policy, but will provide evidence on which to base policy decisions when the need for action arises.
Conditional Basic Incomes—One of the arguments against UBI is that a large proportion of the population simply don’t need or want it and that the money would make little difference to them. To address this, a conditional scheme would make payments available to those below a certain income level as a top-up to get them to a guaranteed earnings level. This could replace a lot of unemployment and work-related benefits, be available to all to apply, and administered in a fairer more transparent way with AI ensuring equitable treatment for all.
Community Service UBI—Under this model, the receipt of UBI would be tied to the individual undertaking some form of community service reinvestment. With public sector budgets being cut in many places and declining provision of services such as libraries, health visitors, and maintenance of public spaces, UBI could be delivered in the form of community grants meant to counter austerity measures. In return for the receipt of UBI, individuals would choose service projects (community gardens, walking trails, artwork, etc.) that would deliver a public benefit, give the individual a sense of purpose and achievement, create new connections, and enable the acquisition of new skills.
Such schemes could also be supported with technology that encourages local programs that promote socialization: clubs, groups, hobby networks, for example, that encourage people to get away from screens and spend time with their neighbors. Overall, this idea is about using UBI to build civic culture and counter the negative impacts of technology on communities. This may mean rethinking how technology is used to bring people together and making the most of it. Another approach would be for individuals to pool their UBI to start and run these programs themselves—which might help them qualify for additional funds and resources for their projects.
Guaranteed Basic Products—Some might call this a modern-day version of food stamps. Under this model, which might run alongside some form of UBI, all that were eligible would receive credits to be used on key products such as clothing and healthy foodstuff from a range of stores. Government might seek to use such a measure to tackle critical food-related health issues in society. So, for example, certain unhealthy products might be excluded selectively or universally on a health basis. Hence, diabetics might be completely excluded from purchasing anything adversely indicated for them.
Guaranteed Basic Services—Here, those who claim the option could receive services free at the point of consumption—from travel and all forms of healthcare through to water, electricity, and gas. Again, governments might use such measures to nudge desirable societal health and environmental behaviors—through free gym access and free public transport as an alternative to private vehicle ownership.
Funding the Transition
The experiments suggested here have not been costed as they could be applicable to nations across the globe and the experimental models adopted for similar ideas might vary dramatically. Our view is that doing nothing is not an option. The population needs to see governments facing up to radical shifts in society with investment in equally radical policy experiments. Here are a few examples of what could be done.
Robot Taxes—A lot of the potential issues around the introduction of AI and other disruptive technologies will arise from the choices made by employers. Will they retain the staff freed up by technology or release them in pursuit of cost saving and higher profits? While we cannot and do not want to hold back innovation, there is a need to explore how to fund the resulting social costs. One option being proposed is the use of so-called robot or automation taxes. Here firms would pay a higher rate of taxes on the profits they derive from increased automation. This has met with a lot of opposition from businesses and many economists but has some support from technology pioneers in Silicon Valley.
Tax Enforcement—A less radical option would be for governments to start using technologies such as AI to beef up enforcement and collect what they are rightly owed under the law. Globally, governments are struggling to fund their current commitments and many services are overstretched. There is also strong opposition to raising taxes to fund service improvement. However, this might not be required if people and companies simply paid what they are legally supposed to and didn’t use avoidance mechanisms. For a fixed period of time, loopholes, avoidance opportunities, and so-called “negotiated sweetheart deals” would be abolished. Using AI, governments would systematically check every individual and business to ensure they were paying what they should do under the law and collect retrospective debts going back as far as the law would allow.
The New Tax Collectors—Rather than recruiting more tax inspectors, government could outsource collection to lawyers and accountants who would do the investigations on a “no win, no fee” basis—investigating those that are not their own clients. Having advised for years on how to avoid tax, they know where to look for the gold. They could be assigned lists of targets to go after and paid a proportion of the fees collected. Of course, they might also generate fees from advising their clients on how to deal with such investigations.
Taxation at the Point of Purchase—Large companies, particularly those in the technology arena, have often avoided paying taxes where the transactions are undertaken. Instead, they have issued invoices and reported their profits in a different lower tax location. Simple rule changes would require firms to pay the tax in the markets where the clients reside. Again, tax lawyers and accountants would be able to provide long lists of reasons why this is not such a simple move. However, as this would be an experiment, we could find out quite quickly what the potential gains and issues might be.
Delegitimizing Tax Havens—A more drastic measure would be to ban all use of offshore tax havens and tax avoidance schemes. A short grace window would be provided for citizens to bring their money back onshore to be subject to national taxation rules. Those who failed to conform would be faced with hefty penalties.
Higher Rate Taxes for a Fixed Period—Of course, the above measures may not work to provide the funds needed for the proposed measures. If so, then the targeted application of increased taxes to higher earning individuals and businesses could help provide the interim funding to finance the measures described above and in the previous chapter.
Bold Experiments and Courageous Leaders
There are no magic beans or money trees that can fund the costs of helping economies transition to the next model that serves the whole of society. At the same time, fundamental changes are taking place that will render people unemployed, and there is the potential for large-scale job loss if the more dramatic forecasts about the impacts of AI come to fruition. To avoid a medium- to long-term crisis, we need to be experimenting now with a range of policy measures to raise skill levels, generate new employment opportunities, and support those who lose their jobs in the transition process. Clearly these policy measures will require investments—these need to be offset against the potential costs of large-scale unemployment and a decline in global competitiveness. In the search to secure the future there are no guarantees—only bold experiments backed by leaders with the courage to pursue them.
- How might we replace work with meaningful activity for the technologically unemployed?
- What issues beyond funding do we need to consider in making the transitions from this economy to future ones?
- What do we do to change the “sit and hope” mentality, and create an experimental mindset, that values trial and error?