Policy conversations and the language of information
Phuah Eng Chye (22 June 2019)
Policy conversations are bogged in a quagmire. Economies muddle along as economists debate the consequences of sustaining quantitative easing and fiscal stimulus. In the meantime, the public wonders if policy-makers are out of touch with their needs. Widespread public dissatisfaction increases the risks of “populist” policy reminiscence; a choice between bringing back the “good old days” of the middle class and manufacturing jobs or the “bad old days” of taxing the rich and breaking up the new “platform” monopolies. Yet neither policy approach seems adequate to providing the solutions that can address the landscape challenges.
Despite the stagnation, participants are generally reluctant to depart from script. Participants are well versed with the playbook and can easily recite the talking points. Often the conversation helps put food on the table. For example, the narratives of central banks and Wall Street support the supply of liquidity and profits to markets and the finance industry. The private sector enthusiastically blames over-regulation for hurting competitiveness because it allows them to shift the blame to the government and to extract even more concessions (less taxes and regulation, more protection and incentives). At other times, the conversations are intended to navigate the path of least resistance and to minimise friction. The drawback of policy conversation reruns is that the same old suggestions will be repeated.
It is extremely difficult to shift the policy conversation. Nobody knows where the new conversations could lead to. They could sow disorder, undermine legitimacy and screw up “team dynamics”. Participants could lose their bearings, suffer missteps, become disenfranchised or upset their income apple cart. New conversations are thus greeted with suspicion and resistance. But there is no way around the fact that discovering new solutions require having new conversations.
More specifically, the problem with the existing policy conversations is that they do not readily talk to the challenges of an information-driven landscape[1]. At most, information effects are treated as a subset of traditional frameworks[2] rather than as a driver of structural change. Hence, information is analysed in relation to traditional frameworks for jobs, skill sets, industries or markets (information asymmetry, search costs, signalling, contracts, efficiency, externalities and welfare).
My suggestion is to recast the policy conversation within the context of the information society. However, it is challenging to amalgamate the language of information into mainstream frameworks. In this regard, the mainstream frameworks are built on organisational concepts from a physical environment that is linear, sequential, hierarchical and centralised. In contrast, the language of information draws its essence from organisational concepts from a virtual environment that is non-linear, non-sequential, non-hierarchical and distributed. The information vocabulary is filled with concepts such as intangibility, size, speed, transparency, modularity, polarisation, convergence, transience and autonomy. It is also difficult to distil information into a simple philosophy. Given the multi-dimensional nature of information[3], there are numerous approaches to interpreting societal evolution. Here are a sample.
Keith R. Hermann theorized that successive advances in coding technologies can be used to explain economic cycles dating back to the 12th century. In this context, innovations that “directly encoded information (printed) in a fashion that allowed ideas to spread more quickly…furthering the ability to compute and transfer information, at ever increasing rates”. He divided the advances into seven encoding waves: The printing wave (starting from the 11th century), mechanical computing (17th century), telegraph (1833), electromechanical computing (1930), internet wave (1980), cloud (2006) and AI (2017).
Source: Keith R. Hermann “Seven waves of code. Towards a universal economic theorem”.
On a slightly different tack, Frank Diana views societal evolution as the outcome from the intersection of building blocks of technological innovation. He notes the speed of technological innovation and adoption will accelerate “with an endless supply of building blocks fuelling rapid value-creating combinations”.
Source: Frank Diana (16 February 2017) “Intersections promise to drive multiple paradigm shifts”.
In relation to AI, Kai-Fu Lee frames technological progress within four waves. “The first two waves – Internet AI and Business AI – are already all around us, reshaping our digital and financial worlds…tightening internet companies’ grip on our attention, replacing paralegals with algorithms, trading stocks and diagnosing illnesses. Perception AI is now digitising our physical world, learning to recognise our faces, understand our requests, and see the world around us. This wave promises to revolutionise how we experience and interact with our world, blurring the lines between the digital and physical worlds. Autonomous AI will come last but will have the deepest impact on our lives…self-driving cars…autonomous drones…intelligent robots…will transform everything from organic farming to highway driving and fast food”.
Other approaches[4] include sociological perspectives[5] which derive important principles from studying the changing characteristics of information while technologists and science fiction writers contemplate futuristic scenarios such as technological singularity[6] – “a hypothetical future point in time at which technological growth becomes uncontrollable and irreversible, resulting in unfathomable changes to human civilization” or superintelligence in the form of “a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds”. We also should not overlook the critical non-technology contributions of codified information such of laws, standards, agreements, norms and knowledge that are necessary to facilitate the effective and efficient use of information.
Each analytical perspective offers their unique insights on the trajectory of information disruption. In this context, the expansive and immersive language of information stands in stark contrast with the staleness of conventional policy conversations. The yawning gulf indicates the difficulty of reconciling the language of information with the mainstream economic frameworks. Nonetheless, there are tremendous benefits in using the language of information as an analytical paradigm as it will bring home the realities of information-driven trends as well as open up new paths of thinking. For example:
- Modularity. The structural shift towards modularity has transformed society from a family and relationship-based community into a diverse community of individuals. This shift is associated with demographic aging and increasing monetisation (i.e. rising living costs). This raises questions as to whether policies suited to large families and industrial development (such as on SMEs) are appropriate for individuals in the information society. In addition, population densities have simultaneously concentrated (crowded) into some cities and fragmented (depopulation) elsewhere. Past policies to develop rural areas may no longer be appropriate while affordability and house ownership may no longer be viable objectives in cities experiencing crowding.
- Intangibility. The decline of the manufacturing sector reflects the physical aspects of an economy is shrinking in the transition to an information society. Therefore, there is a need to develop alternative models built on intangibility; reflecting that the consumption of physical products is saturated. There are many interesting questions. (1) Since physical output is no longer a key consideration, what should be the policy objectives? (2) What would constitute growth? (3) What would be the difference between wage-driven and profit-driven growth? (4) What are the constraints on its growth? (5) How would one model the relationships between investment, consumption, wages, profits, inflation, costs and asset prices? (6) A high-information economy naturally imports its physical goods from lower-income economies. How will it finance these imports? It is evident the growth process for an intangible economy[7] is different from a physical economy. There is less need for capital and labour. This implies the private sector will generally be net lenders rather than borrowers. The level of activities will be determined by the ability to monetise value subject to the financial stability constraint. The duration of growth will be determined by the ability to keeping income circulating within the economy. The ability of the intangible economy to grow using less resources, labour or capital suggests sustainability goals are achievable through policies that seek to minimise, rather than maximise, the use of physical resources. Economic models could also be re-oriented to maximise the use of human capital.
- Regulations. Regulations designate the boundaries for public and private control over communications, data, content, ideas, brands and talent. Information disrupts traditional organisations and boundaries and diminishes the clarity of legal definitions. This gives rise to more disputes and creates the need for more regulations which in turn increases complexity. The increasing value of information and communications will intensify the battle for control of ideas, infrastructure and information flows. But value in information-based activities (monetisation, participation, communications, reputation and law) is generated by broad participation and autonomous processes. How are private ownership rights to be asserted over assets (including data) that are intangible, abundant, shared and global in nature? Should the priority be to protect private ownership to provide incentive for innovation or to maximise cooperation (to innovate) through broadening distribution of the benefits? This is particularly relevant at the global level where standardisation and common norms are crucial to promote mass adoption and scalability. A breakdown of cooperation among nations will trigger deglobalisation.
- Values and relationships vs autonomy. The information society is individualistic, autonomous, transient and diverse. These features indicate relationships, traditional values and institutions will be substituted by autonomous and information-driven cooperation (e.g. stranger sharing). Over the long-term, it is unknown how societies will evolve given the vacuum in relationships and values. In the absence of a new ethos, the risk is that the traditional institutions and elites will use automation, supported by force, to reassert values to defend the traditional order. The shaping of shared values is a major challenge in an autonomous environment.
Overall, it is timely to reconcile policy conversations[8] with the language of information.
There are two main considerations. The first is that the language of information is also the language of organisation. Hence, organisational issues should be at the centre of policy thinking. This provides an opportunity to reassess policy goals and regulations in relation to the changing landscape. The second is to develop new macroeconomic models that more realistically portray how an information-driven economy works.
References
Frank Diana (2019) “Reimagining the future: A journey through the looking glass”. Tata Consultancy Services Limited. https://frankdiana.net/reimagine-the-future/
Frank Diana (22 January 2019) “Acceleration”. Reimagining the future. https://frankdiana.net/2019/01/22/acceleration/
Frank Diana (16 February 2017) “Intersections promise to drive multiple paradigm shifts”. Reimagining the future. https://frankdiana.net/2017/02/16/intersections-promise-to-drive-multiple-paradigm-shifts/
James Gleick (2011) The information: A history, a theory, a flood. Pantheon Books.
Joseph E. Stiglitz (September 2017) “The revolution of information economics: The past and the future”. NBER. https://www.nber.org/papers/w23780.pdf
Keiichiro Kobayashi (8 March 2019) “Future design: A new policymaking system for future generations”. https://voxeu.org/content/future-design-new-policymaking-system-future-generations
Keith R. Hermann (1 February 2019) “Seven waves of code. Towards a universal economic theorem”. Science Spotter. http://www.sciencespotter.com/spottingscience/2019/2/1/seven-waves-of-code-towards-a-universal-economic-theorem
Kai-Fu Lee (2018) AI Superpowers: China, Silicon Valley and the new world order. Houghton Mifflin Harcourt.
Phuah Eng Chye (2015) Policy paradigms for the anorexic and financialised economy: Managing the transition to an information society.
Phuah Eng Chye (2 September 2017) “The services economy: Comparing the manufacturing and service paradigms”.
Phuah Eng Chye (16 September 2017) “The services economy: Service sector growth and the information society”. http://economicsofinformationsociety.com/the-services-economy-service-sector-growth-and-the-information-society/
Phuah Eng Chye (27 April 2019) “Defining the information society”.
Phuah Eng Chye (11 May 2019) “Critique of information”.
Phuah Eng Chye (25 May 2019) “How information alters economic concepts”.
Phuah Eng Chye (8 June 2019) “The information society landscape”.
Silvia Merler (16 July 2018) “Economy of intangibles”. Bruegel.
[1] Phuah Eng Chye “The information society landscape”.
[2] Joseph E. Stiglitz provides an excellent overview on the the impact of the economics of information on traditational theoretical frameworks. Silvia Merler provides a review of the economic analysis of intangibles based on traditional frameworks.
[3] James Gleick provides a historical perspective on information.
[4] “Defining the information society”.
[5] “Critique of Information”.
[6] https://en.wikipedia.org/wiki/Technological_singularity
[7] “The services economy: Comparing the manufacturing and service paradigms”; “The services economy: Service sector growth and the information society”.
[8] Keiichiro Kobayashi discusses the concept of ‘future design’ – where people are asked to become an imaginary future generation and to think and act in the interests of that generation – and how it might be incorporated into policymaking.