Technological innovation

In immediate responses to the COVID-19 crisis, science and innovation are playing essential roles in providing a better scientific understanding of the virus, as well as in the development of vaccines, treatments and diagnostics. Both the public and private sectors have poured billions of dollars into these efforts, accompanied by unprecedented levels of global cooperation. However, the economic crisis that is currently unfolding is expected to severely curtail research and innovation expenditures in firms, while debt-laden governments will face multiple, competing demands for financial support. These developments threaten to cause long-term damage to innovation systems at a time when science and innovation are most needed to deal with the climate emergency, meet the Sustainable Development Goals, and accelerate the digital transformation. Governments will need to take measures to protect their innovation systems as part of their stimulus and recovery packages, but should also use these as opportunities for reforms. In particular, science, technology and innovation (STI) policy should shift towards supporting a more ambitious agenda of system transformation that promotes a managed transition to more sustainable, equitable and resilient futures.

In tandem with the diffusion of computer technologies, labour markets across the OECD have undergone rapid structural transformation. In this paper, we examine i) the impact of technological change on labour market outcomes since the computer revolution of the 1980s, and ii) recent developments in digital technology – including machine learning and robotics – and their potential impacts on the future of work. While it is evident that the composition of the workforce has shifted dramatically over recent decades, in part as a result of technological change, the impacts of digitalisation on the future of jobs are far from certain. On the one hand, accumulating anecdotal evidence shows that the potential scope of automation has expanded beyond routine work, making technological change potentially increasingly labour-saving: according to recent estimates 47 percent of US jobs are susceptible to automation over the forthcoming decades. On the other hand, there is evidence suggesting that digital technologies have not created many new jobs to replace old ones: an upper bound estimate is that around 0.5 percent of the US workforce is employed in digital industries that emerged throughout the 2000s. Nevertheless, at first approximation, there is no evidence to suggest that the computer revolution so far has reduced overall demand for jobs as technologically stagnant sectors of the economy – including health care, government and personal services – continue to create vast employment opportunities. Looking forward, however, we argue that as the potential scope of automation is expanding, many sectors that have been technologically stagnant in the past are likely to become technologically progressive in the future. While we should expect a future surge in productivity as a result, the question of whether gains from increases in productivity will be widely shared depends on policy responses.

The rapid technological progress in automation, robotisation and artificial intelligence is raising fears, but also hopes, that in the future the nature of work will change significantly. There will be changes in what we do, how we form workplace relations, how we find work and the role of work in a society. Some believe that these changes will be for the better: we will need to work less and thus will have more free time. Others think that the changes will be for the worse: there will be fewer ways to earn a living. The central question of this paper is this: will adages such as ‘By the sweat of your brow you will eat your food’ and ‘No bees, no honey, no work, no money’ become obsolete? Will work disappear and with it the societal relations and inequalities that result from differing success in work? If this is going to happen, what policy options do we have to address the issue?

Global food systems today are in need of transformation. Billions of people are poorly nourished, millions of farmers live at subsistence level, enormous amounts of food go to waste and poor farming practices are taking a toll on the environment. Achieving the Sustainable Development Goals (SDGs) by 2030 will require food systems that are inclusive, sustainable, efficient, nutritious and healthy.
Achieving a true transformation of food systems requires a holistic approach – one engaging all stakeholders and deploying a wide array of actions such as improved policy, increased investment, expanded infrastructure, farmer capacity-building, consumer behaviour change and improved resource management. Technology innovations, combined with other interventions, can play an important role in enabling and accelerating food systems transformation.

In addition to reporting major trends and patterns observed in global fisheries and aquaculture, this edition of the "State of World's Fisheries and Aquaculture" scans the horizon for new and upcoming areas that need to be considered to manage aquatic resources sustainably into the future, including cooperation through regional fisheries bodies and advances such as blockchain technology.

The focus of this report is on harnessing AI systems today, and as they evolve, to create maximum positive impact on urgent environmental challenges. It suggests ways in which AI can help transform traditional sectors and systems to address climate change, deliver food and water security, protect biodiversity and bolster human well-being. This concern is tightly linked with the emerging question of how to ensure that AI does not become harmful to human well-being.

Automation is an idea that has inspired science fiction writers and futurologists for more than a century. Today it is no longer fiction, as companies increasingly use robots on production lines or algorithms to optimize their logistics, manage inventory, and carry out other core business functions. Technological advances are creating a new automation age in which ever-smarter and more flexible machines will be deployed on an ever-larger scale in the workplace. In reality, the process of automating tasks done by humans has been under way for centuries. What has perhaps changed is the pace and scope of what can be automated. It is a prospect that raises more questions than it answers. How will automation transform the workplace? What will be the implications for employment? And what is likely to be its impact both on productivity in the global economy and on employment?