The approach to understanding the future of music in Australia is described in general terms in How to Explore the Cultural Future, the second special article about our 2014-15 major project. Number five in the series of special articles deals with the intellectual roots of modern scenario planning, and a parallel approach we discovered elsewhere: Scenarios, Virtual History, and Chaos.
To build scenarios that depict possible futures ranging from “bad” to “best” requires context — lots of it. The music sector is complex and highly dependent on future environments in Australia and abroad which cannot be examined in isolation. Remarkably, we have been unable to find published scenarios which place the arts or any individual artform in the context of alternative global settings. This venture appears to be a first.
Future scenarios 10 and 20 years ahead must start globally for most activities but especially if they are as internationally exposed as music. The digital revolution, inequality between and within nations, technology, climate change and other factors are bound to have a huge impact on Australia — our economy, sustainability and cultural policy, and hence on musical activity. We are part of the global community for better or worse.
The upper part of the scenario model lists global factors as primary, influencing music both directly and through their impact on Australia generally. Uncertainty is what scenarios are all about — we cannot forecast with any confidence at all, not even when we use good old-fashioned sensitivity analysis. But some factors come together, and some are more certain than others. A good scenario synthesises a multitude of underlying driving forces brings into one or two critical uncertainties — factors combine in various ways which then become the ultimate uncertainties. To identify these is a real challenge in scenario planning.
The flow chart to the right shows that the critical uncertainties result from global influences both directly and indirectly through their impact on the Australian economy, culture and environment. Other influences arise within Australia. Finally, the music sector itself generates influences shown by a dotted arrow on the flow chart. The interrelationships are ubiquitous.
The next step is the actual scenario building. We are developing three or four scenario stories, ranging across the spectrum of plausible possibilities from “best cases” to “worst cases”. Since conventional forecasting doesn’t work over a long period, it follows that each version to be at all plausible must be equally likely to eventuate — though once the scenario stories have been written, we can mitigate the outcomes that would eventuate if no action was to be taken.
Further guidance for the scenarios will come from the wealth of recognised issues already identified in the Knowledge Base, and from the insightful responses to our scenario-planning survey we have received since launching the survey in June. We must also recognise the possibility of what may be called possible counter-intuitive implications or findings. A “bad-case” scenario may have some positive impact on the music sector — a tricky feature of scenario work that must be recognised.
Finally, scenarios are “the art of strategic conversation”. The initial scenario stories can only be presented in draft form. The feedback process shown by the yellow box at the bottom left-hand end of the model chart down to the final scenarios is crucial if leaders in the music sector are going to accept (own) these scenarios in their advocacy for the best possible future for music in Australia.
The project is now proceeding along this complex path.
The red block to the upper left of the scenario model envisages seven global change factors which we have identified as possible influences on the future music sector. The influences are listed alphabetically in the red box to the right to show that no single factor is necessarily stronger than any other item on the list. Each of them will have a major influence on the future global society, but the extent and direction of this influence will depend on a wealth of societal, technological, ecological, economic and political factors. Furthermore, the seven sources of global influence are correlated to some extent, so a “bad” future in one will quite possibly be reinforced by “bad” futures in others, and similarly for relatively benign futures. This is captured in the model by the arrow going directly from “global change” to the yellow box of “critical interrelations and uncertainties”.
The green box in the upper right of the model represents four identified groups of general influences within Australia: the economy, cultural policy, net migration, and sustainability. Though derived from the global situation, these items have specific Australian attributes and therefore add further uncertainties to the top yellow box on the chart, and hence to the future of the music sector.
The blue box, finally, shows the direct inputs from the music sector itself (whether influencing the analysis of critical interrelationships and uncertainties as suggested by the dotted arrow in the model chart, or as direct inputs into the writing of draft scenarios):
The list of sources listed below starts with those initiated in Australia, and then notes international sources. Each of the specific Australian scenarios has clear global connotations. Many of these sources cover more than one of the groups listed in the scenario model chart, with a possible bias towards general Australian scenarios and scenarios focusing on the future natural environment. The last item on the list of other sources, on global risks according to the World Economic Forum, is given special treatment in the final main section.
The main topics are climate change, international digital trade, digital development and its impact on particular industries and sectors, and global risks in general. There are also reports on intellectual property scenarios which need to be integrated into the assessments.
The final source listed here is the World Economic Forum’s annual report on Global Risks. It is such an important and all-inclusive analysis that the next section is devoted to the latest report.
This is the prime source on global concerns generally, including some that are not covered above (like global governance, growth and distribution). The World Economic Forum (WEF) has conducted its annual Global Risks Perception Survey since 2006-07, making 2013-14 the eighth. The WEF was founded in 1971 when a group of European business leaders met under the patronage of the European Commission and European industrial associations. During the 1980s it was transformed into a truly global organisation. The Forum is most widely known for its annual meeting of leaders in Davos, Switzerland.
The 2013-14 survey was conducted in October and November 2013 “among WEF’s multi-stakeholder communities of leaders” from business (40.6%), academia (18.3%), non-government organisations (17.0%), international organisations (8.5%), government (7.4%), and other sources (8.2%). Of over 700 respondents, 52% were from advanced economies and 40% from the emerging and developing world (8% unspecified). Females comprised a minority (27.7%).
To capture the voice of youth, the survey also targeted the WEF’s “community of global shapers”. Under-30s accounted for 21.8% of the 2013-14 survey respondents. The survey is as representative as can be expected of a general global sample.
There are three kinds of findings from the survey:
The three illustrations that follow deal with each of these findings in turn.
Eight years of WEF’s Global Risks surveys show a changing but largely consistent list of nominated risks, classified as economic (light blue in Table 1 and the two charts following), environmental (green), geopolitical (gold), societal (red), and technological (purple). Respondents chose among the 31 risks nominated in the 2014 survey, and roughly similar numbers in previous years except for 2012 and 2013 when the decision was made to increase the number of risks to 10 for each of the five main categories. WEF considered the information shown in Table 1 to be consistent enough to be published as a time series in the annual Global Risks report.
The most likely single risk has changed from being economic (“asset price collapse” following the onset of the global financial crisis and still top in 2011) to being societal (“income disparity”). But more strikingly, among the five most likely global risks the environment has grown from not being represented at all in any year up to 2011 to being prominent enough to account for 10 of the 20 most likely risks in 2011 to 2014. The environmental risks have a number of labels though many would be associated with climate change as a unifying factor (including 2012 and 2013 when “rising greenhouse gas emissions” was the term used instead of climate change).
Based on likelihood of occurrence, economic risks in contrast with environmental risks fall from occupying 11 of the 20 the top five most likely nominations in the 2007 to 2010 surveys to showing up only three times in the 2011 to 2014 surveys. The picture is different when impact is considered rather than likelihood as discussed below.
The major category with the smallest number of observations is technology, though cyber-attacks made it into the top five most likely global risks in 2012 and again in 2014. Technology is generally seen as a positive rather than negative force in the world, and therefore less likely to show among the major risks. The two other nominated technological risks in 2014 came nowhere near the total top five: “critical information infrastructure breakdown” and “data fraud/theft”.
The list changes when considering impact. The single top impact risk in each of the eight years of the survey from 2007 to 2014 was economic: asset price collapse in each of the first four years switching to what would be generally fiscal crises from 2011 to 2014. There may have some bias towards economic risks in a sample of respondents consisting of 40.6% business people, though it isn’t major and is unsurprising in an organisation calling itself an economic forum. The ranking of economic factors according to impact in Table 1 actually declined from the 2007 to 2010 surveys when a total of 13 of the top five 20 global risks were economic, to the 2011 to 2014 surveys when the number fell to 10 of 20.
During the same period, global environmental impact risks rose from none in any year from 2007 to 2010 to a total of six of the 20 possible observations adding the survey results from 2011 to 2014.
One type of geopolitical impact risks came third on the list in 2011 (“geopolitical conflict”) and fourth in 2013 (“diffusion of weapons of mass destruction”). “Food shortage crises”, a societal risk, made the list in third place in 2012.
The 2014-15 survey is being conducted in October-November 2014 which happens to coincide with the writing of this article. The world is awaiting the outcome of the West African Ebola crisis (a societal risk) and what can be done. It is considered the worst outbreak of an epidemic disease for decades, caused by genetic change in a virus that has been around for 40 years. In the absence of a vaccine up to now the current strain of Ebola has been fatal to most humans.
We are also witnessing the rapid development of a serious geopolitical risk called Islamic State (IS), also known as ISIS or ISIL (Islamic State of Iraq and Syria/the Levant). Operating in Iraq and Syria it has caused western democracies once again to provide military and other support in an effort to defeat what has developed into a well-equipped terrorist force.
“Pandemics” and “Terrorist attacks” are both on the current WEF lists and could well make it to the top five global risks in terms of likelihood and, quite possibly, impact. As Table 1 demonstrates, the risks change over time. Any serious new development has potential impact, not just where it originates but globally.
Global Risks 2014, published before the Ebola crisis, actually identified “perhaps the oldest form of systemic risk” as that arising from viruses and pandemics which “has entered a dangerous new phase as people and goods move at increasing speeds and over greater distances, with many passing through a small number of airports and other hubs.” (p 26)
The 31 global risks in 2014 form a “landscape” plotted in two dimensions: likelihood along the horizontal axis and impact vertically. Each of the risk were assigned scores on the seven-point scale, and the average scores (4.31 for average likelihood and 4.56 for average impact) were used to divide the landscape into four quadrants. The range for likelihood of each risk was from less than 3.5 to almost 5.5 for likelihood and from about 3.8 to 5.3 for impact.
Chart 1 shows only the upper right quadrant where 10 of the 31 global risks show above-average scores on both likelihood and impact. The size of each plot gives a combined visual impression of likelihood and impact which marks unemployment/underemployment and fiscal crises as the two most serious economic risks; water crises, climate change and extreme weather events as the worst environmental risks; and income disparity as the main societal risk to watch. Cyber-attacks were also relatively likely to occur and to have significant impact if they did; biodiversity loss/ecosystem collapse, food crises and natural catastrophes were closer to the lower left corner of the upper quadrant which covers risks that are above-average on both criteria.
In other quadrants, pandemics were seen as relatively unlikely but having slightly above average impact should they occur; terrorist attacks to be slightly more likely but having less impact. Terrorism remained in the lower left quadrant with both likelihood and impact below average, though not by very much. The highest impacts outside the upper right quadrant were from the technological risk of “critical information infrastructure breakdown” (considered relatively unlikely), followed by “political and social instability” and “failure of financial mechanism or institution”, both of which were rated just below average likelihood. “Global governance failure” was also rated as having above-average impact and was only slightly less likely to occur according to the 2014 survey.
Asking respondents to nominate between three and six pairs of interconnected global risks brings out some important new perspectives. Chart 2 suggests that some global risks are clearly interconnected, others less so. The strength of each interconnection is shown by the thickness and colour of each line: the strongest thick dark blue lines are centred on fiscal crises and unemployment — which has another strong link with income disparity. There is another strong — and unsurprising — link between climate change and extreme weather which is not directly connected with other strong neighbouring links.
Light blue lines also indicate strong connections, and the thinner brown lines are significant too. The total picture that emerges from the three coloured interconnection lines in conjunction is the link between the three main risk nodes — centred on global governance failure linking to fiscal crises and unemployment in one direction and climate change and its associated risks in the other.
Global Risks 2014 draws two main conclusions from the interconnections map, both associated with the cluster around global governance failure, fiscal crises, and political and social instability:
Instabilities in an increasingly multipolar world : “Domestic pressures are denting both the appetite and the ability of advanced economies to maintain that authority on the global stage. Large emerging-market countries are keen to play a significant role but are struggling to reconcile rapid economic growth, domestic social change and complex political reform. At the same time, global multilateral institutions are finding it hard to achieve consensus, and thus concerted action, on critical matters due to the proliferation of assertive, discordant voices. [The chart] shows how the failure of global governance is connected with other risks.” (p 27)
Generation lost highlights the connections between unemployment, fiscal crises, political and social instability, income disparity and global governance failure — much the same risks that were identified above.
The focus on young people is worth quoting in full: “Around the world, the generation coming of age in the 2010s is most affected by the legacy of the financial crisis and slow economic growth. In many countries, dramatically high unemployment is frustrating young people’s efforts to earn, generate savings, gain preferential experience and build careers. Traditional higher education is even more expensive and its payoff more doubtful. These issues need to be addressed inclusively on local, national and global levels to minimize the risks of a breakdown in social cohesion and enduring loss of human and economic potential.
In general, the mentality of this generation is realistic, adaptive and versatile. Smart technology and social media provide new ways to quickly connect, build communities, voice opinions and exert political pressure. This generation of digital natives is full of ambition to make the world a better place, yet feels disconnected from traditional politics and government – a combination which presents both a challenge and an opportunity in addressing global risks.” (p 33)
Importantly, Global Risks 2014 shows a separate chart for both under-30s and women respondents (as noted previously 21.8% and 27.7% of the total number of respondents, respectively). These groups were considerably more concerned about global risks than older people and males.
The gender difference is highly significant (p 18). Women rated the highest impact to come from water crises with a score as high as 6.2 on the seven-point scale. They rated climate change second (5.9) followed by biodiversity loss/ecosystem collapse and unemployment/underemployment (both about 5.7), extreme weather events (5.6), fiscal crises (5.5), income disparity (5.3), political and social instability (5.2). These eight risks were all rated above five by the women.
The comparable scores for males were water crises 4.7 (the largest gender difference with women averaging 6.2), climate change just below 5.0 (almost a full point on the seven-point scale less than females), biodiversity loss and ecosystem collapse 4.6 (more than a full point below the finding for females), unemployment 4.8, extreme weather events 4.7 (almost a point lower than the average for females), fiscal crises 5.3, income disparity 4.7, and political and social instability 4.6.
Females saw every one of the 31 identified global risks as more serious than the males did. Males came close in only three cases: pandemics and weapons of mass destruction about a percentage point and the technological risk of critical information infrastructure breakdown about two percentage points. The observation for pandemics doesn’t quite fit what one might expect and a larger difference might show in the next survey given the coincident timing of the 2014-15 survey and the growing perception of the Ebola epidemic. Among the eight major risks all scoring above five for females, only one, fiscal crises, scored above five among males, though climate change came close. Women generally rated environmental and societal risks much more seriously than males.
There are also considerable differences between people under 30 and 30-plus. For each of the 31 global risks the younger respondents saw the greater threat (p 19). Of the eight scoring five or more, water crises led among the under-30s with a score of 5.9, followed by fiscal risks (5.6), unemployment/underemployment, climate change and biodiversity loss/ecosystem collapse (each 5.5), extreme weather events (5.4), weapons of mass destruction (5.2, but likelihood considered relatively low), and failure of financial mechanism or institution (5.0).
People aged 30 or more scored the impact of water crises at just below 5.0, fiscal crises at 5.3 (the highest score among the 31 global risks for this group though still below the 5.6 for under-30s), unemployment and underemployment just below 5.0, climate change 5.1, biodiversity loss and ecosystem collapse much lower than the younger group at 4.7, extreme weather events 4.6 (ditto), weapons of mass destruction again low likelihood but impact scoring 4.6, and failure of financial mechanism or institution 4.6.
The picture may be marginally less clear than for the genders, but the environmental scores are still significantly more pessimistic among the under-30s. Unemployment and underemployment are also matters of high concern with the group of younger people, who are close enough in age to be highly conscious of youth unemployment, though presumably reasonably safely employed themselves.
Hans Hoegh-Guldberg. Entered on Knowledge Base 17 October 2014. Revised 9 November 2014 after developing updated music sector scenario model.