The word digitalisation is on its way to become a buzzword that is not only used by techies but also by development professionals around the world. Just two years ago, in 2016, the World Bank devoted the World Development Report (WDR) to Digital Dividends, referring to the distribution of digitalisation benefits to a broader population. The WDR suggested inclusion, efficiency, and innovation as the main mechanisms through which digital technologies can promote development.
The potential is enormous and covers a plethora of sectors, from finance, industry, and agriculture, to education and political participation. However, is digitalisation the panacea to achieve a broader set of development goals such as those included in the Agenda 2030? The answer to this question depends on which drivers underpin technological change.
Digitalisation vs. Exponential Technological Change
The concept of technological change is much broader than digital change or digitalisation – i.e. converting information in ways that are readable by a computer and usable for intelligent purposes. The main reason is that, even when digitalisation is often analysed on its own and used to refer to a limited number of technological applications (mainly mobile phones, internet and, more recently, big data), it has underpinned exponential changes in other areas of technological development. Increased computing capacity at lower costs has favoured innovations in nanotechnology, biogenetics, optics, neurology, chemistry, robotics, and artificial intelligence, among many other areas.
Digitalisation has in fact favoured a tree-like system of technological change that boosts innovations across different fields. An example is the convergence and synergy between digitalisation, nanotechnology, and biogenetics, triggering significant progress in medical diagnosis.
Following Niklas Luhmann, the system is autopoietic: innovation itself bring more innovation. The system of technological change features a positive feedback mechanism and yields outputs that increase exponentially. In other words: Innovation brings about twice as much innovation, not only within the field of digitalisation but across many other fields, and so on. This is what we call exponential technological change (ETC).[1]
Market-Driven vs. Development-Driven ETC
Without adequate governance, the practical applications of ETC will most likely respond to market needs and not necessarily to broader human development goals. Many contributions of digital technologies to date are centred on fostering productivity, efficiency, and growth. This applies to both economies in the Global North and economies in the Global South. Digital platforms may be supported by data mining tools and weak artificial intelligence (A.I.),[2] useful for identifying behavioural patterns and understanding the profile of consumers. This allows the supply of a broader variety of goods and services that are individually tailored at lower costs, benefiting consumers around the globe.
The fact that ETC is often profit-driven is not necessarily bad news for the achievement of sustainable development goals (SDGs). However, the net costs and benefits depend on a number of factors. For example, ETC is already triggering automation in many industries. This phenomenon has increased labour productivity in some cases; but in others, especially for manual and repetitive tasks, labour has actually become redundant. Depending on the country, between 50% and 85% of current jobs will disappear or will be transformed in the next decades due to automation. Any replacement requires a different set of skills, placing a high importance on education and training systems.
If societies are not ready to cope with short-term technological unemployment, this could increase current income inequalities, cancel benefits, fuel nationalist movements, undermine global governance, and thus overall hamper the achievement of sustainable development goals (SDGs).
As a general rule, when ETC is market-driven it requires
- designing better regulations at the global level (to avoid concentration or at least to make sure that concentration does not create broader socioeconomic inequalities),
- public-private partnerships (to make possible applications of ETC which are more accessible), and
- to support technological training while maintaining a human-centred education, which is vital so that individuals remain citizens, able to flourish in more comprehensive ways than simply as technological users and consumers.
Development-driven ETC tends to be citizen-oriented. Examples include the use of digital technologies to increase government transparency, the application of weak A.I. to improve urban management, or cheaper apps that allow medical diagnoses among vulnerable groups.
The Challenges for Global Governance
The difference between market-driven and development-driven innovations will become even more relevant in the next decades. Exponential innovations will continue to be so complex and dynamic that a number of unexpected breakthroughs could happen across different technological areas. Depending on public policies, international cooperation, knowledge-sharing, and global governance agreements, this could mean that innovations are only available for very few individuals with market power or that benefits are somehow shared more universally.
In the case of more universal sharing, with a more even distribution of ETC benefits, we could achieve many SDGs and witness a generalised raise of living standards among the global population. But this scenario will depend on pushing forward a broad cooperation agenda to maximise the benefits of ETC and minimise the adjustment costs. For example, states, corporations, and other non-state actors will need to cooperate closely to find ways to protect intellectual property rights, promoting innovations competitively and yet, allowing universal access. Cooperation will also be necessary to identify ways to prize development-driven vis-à-vis market-driven innovations without hindering innovation altogether.
[1] I owe the concept of ETC and some ideas on its associated challenges and opportunities to José Ramón López Portillo. See López Portillo (2018), La gran transición. Retos y Oportunidades del Cambio Tecnológico Exponencial, FCE and CONACYT, Mexico.
[2] Weak artificial intelligence, or A.I. for specific purposes, refers to computing processes that are designed to solve problems within specific contexts and to optimize specific tasks. In contrast, strong A.I. or general-purposed A.I., includes the ability to learn and apply intelligence across different fields.
1 comment