Nesta is a UK NGO interested in, among other things, innovation. They have just produced a very useful report about foresight – Don’t stop thinking about tomorrow. If you want a good short overview of benefits and challenges associated with futuring, I recommend it.

The authors re-iterate the point that prediction isn’t the only, nor most useful, objective for thinking about the future. It is often more effective as a planning tool, enabling organisations, communities or countries to help shape the future or to be better prepared for (un)surprising events. They emphasise that governments and firms need foresight capabilities to help address systemic challenges, and illustrate some of the different and evolving foresight approaches countries and businesses are taking.

A torch analogy is used to illustrate the identifying plausible, probable and preferable futures.

One of the most interesting parts of the report for me was the interest that designers are taking in foresight to help people get more engaged. The report highlights one firm, Superflux, which has been working with a range of organisations to help make thinking about the future more tangible. Examples of their projects, including tarot cards for creating scenarios, can be found here. [NZ's Landcare Research has also produced a card set for similar purposes].

Stuart Candy, who works for Arup, a design and engineering consultancy, points out the similarity between foresight and design processes. Both he and Superflux stress the importance of involving designers in futures exercises (“design futurescaping” or “experimental futures”) to both explore the range of futures and identify the preferred ones.

As Stuart Candy says

Innovation without foresight is dangerous. Foresight without innovation is pointless.

I’m not aware of design studios, or university design departments in New Zealand, being actively involved in foresight to this extent. But I’d love to talk with you if you are, or would like to be.

The essay by John Beddington,  the former UK Chief Science Adviser, considers the art of effective science advice. He cautions that calls for “evidence based policy” aren’t necessarily simple and that  policy making isn’t science. Geoff Mulgan gives examples of “randomised control trials” in policy making and notes that the most influential advice isn’t necessarily that which is the most logical, or comes from the cleverest people.  What matters more is whether the adviser is trusted and reliable, and that the advice fits the cognitive style of the receiver.

The UK is also examining what works in relation to social policy.

So plenty of experience for NZ to tap into.

Firstly, what is a social entrepreneur? Ashoka, the largest network of social entrepreneurs, defines them as

…  individuals with innovative solutions to society’s most pressing social problems. They are ambitious and persistent, tackling major social issues and offering new ideas for wide-scale change.

Social entrepreneurs have gone by that name since 1980, so it is more than a fad. Universities offer courses and centres on social entrepreneurship. Some may view that as a sure sign that it is an historical artifact of no current utility. But the Grameen Bank and Muhammad Yunus won the 2006 Nobel Peace Prize for their microfinancing initiatives [Yunus' wikipedia entry also touches on some of the controversy surrounding Yunus and the bank, much of which seems politically motivated].

McKinsey & Company have now also produced a series of essays on social entrepreneurship, in recognition of a decade of activity by the Skoll World Forum. You can read a brief piece in Forbes, or browse the essays.

What struck me looking at some of the essays and contributors is the growing maturity of the activity and the diversity of people and organisations involved. There is the recognition that helping one village develop a supply of safe drinking water (or books for the school, etc) is good, but real impact only comes if you can repeat that for many villages. And scaling up social ventures is incredibly challenging.

The examples of social entrepreneurship aren’t just about individuals or NGOs with a social conscience filling in gaps ignored by governments. Companies, and in some cases government agencies, are also becoming involved. For some of the companies they have found helping create a solution to a problem in a developing country leads back to benefits in the products or services they provide in developed countries. And there is a growing focus on being able to measure and demonstrate success.

What’s going on in social entrepreneurship here? Not a lot. Massey University has established the New Zealand Social Innovation and Entrepreneurship Research Centre, but that’s at the thinking rather than doing end of social entrepreneurship.

The NZ Centre for Social Innovation ceased most of its activity this month because of a lack of investment.  Faye Langdon, a trustee of the Centre, noted that there are a lot of small scale initiatives going on in NZ, but not much willingness to collaborate at this stage. She also noted that Canada and Australia have greater government and private sector support social entrepreneurs. But having entrepreneurs too reliant on government support strikes me as the kiss of death for such enterprise, and demonstrates a certain lack of entrepreneurial initiative. The Whanau Ora scheme had the potential to develop social entrepreneurship, but that seems increasingly unlikely as political and media attention focus on finding failures within it.

As with other types of innovation in NZ, the social kind is hard work. But in these challenging times its up to individuals to take the initiative.

The video on Fiscal policy, fairness between generations, and national saving looks at different options for creating fair intergenerational fiscal policy.

The presentation on Demographic balance and human capital from an intergenerational perspective examines how population structures are changing in ways other than just age, and discusses the implications for productivity as well as adaptive capabilities and vulnerabilities in relation to climate change.

“the baby boomer generation is constructing a future that will leave problems for subsequent generations”.

Paul didn’t directly respond to this question in his lecture, but I got the sense that his view is that policy makers are too passive with respect to migration and they should be more actively constructing  sensible and forward looking migration and population policies so that there are fewer problems for our descendants to clean up.

If you replace “the baby boomer” with “your” I also think Paul’s son’s complaint is one uttered every generation by offspring to parents.

This timeless conflict between younger and older generations is also illustrated by this rather unhelpful video posted on the McGuinness Institute website made by some of the LongTermNZ participants. There are valid reasons to be worried about what is now being called intergenerational equity, and it has got some international business leaders attention [PDF].  But setting up a contrived Them versus Us conflict is not constructive, although it is one way of getting people interested in a topic.

New Zealand’s National Institute of Demographic and Economic Analysis, based at the University of Waikato, has produced a good report examining New Zealand’s demographic forces and what population ageing [really] means [PDF] (they also have a range of other excellent reports and data sets available for thought provoking perusal).

As Paul Spoonley suggests, more time needs to be devoted – by all of us, not just policy makers & demographers – to thinking about New Zealand’s future population trends and characteristics and actively creating fair and equitable policy and actions for all.

However, Wired has an article on the future of 3D printing (aka additive manufacturing) that is less bullish about it being the future of manufacturing. While exhibiting plenty of growth potential, the report endorses an earlier Deloitte analysis that concludes that while many people will soon be able to buy their own 3D printer, they won’t be setting up their own manufacturing company. This is largely due to the costs or access to materials to replace many household objects, and the inability to scale up production. As with current home printers, the costs of the consumables rather than the printer will be the limiting factor.

Many large corporations, such as Boeing, are already using the technology to produce prototypes, which are then manufactured by more conventional means. And new services are likely to pop up so you can go and get a replacement part at your local garage or home maintenance store. Remember when you could buy a new element for your kettle rather than having to buy a new kettle? Maybe those days will be coming back.

As an article in Slate noted  one of the longer term benefits of cheap 3D printing may be to help inspire school students to think about industrial design. However, such classes will need to have a stronger theoretical and intellectual underpinning than the woodwork and metal work classes I took at school to have a more revolutionary effect. Taking home crude plastic rabbit sculptures and other doodads to show mum & dad won’t cut it.

Due to costs 3D printing probably won’t have the same influence or reach as Meccano, which reputably inspired several generations of physical scientists and engineers. But it, along with other aspects of “maker” and “hacker” culture are likely to influence how the current and next generation think about manipulating the physical world and designing futures.

A somewhat tongue-in-cheek view of future developments in 3D printing to keep an eye out for is also available on the Wired website.

Increasingly, as with many other areas, data crunching is being used to attempt to predict the future, or at least help to do so. Media reports are starting to use the term “Nate Silver” as a verb when discussing data analytics. There is an expectation, or hope, by some that with more data and sophisticated analyses will come more accurate predictions.

Recorded Future provides a service where data (media reports, tweets, analyses, etc from the internet) on particular topics or issues (such as whether electronics manufacturer Foxconn will move production away from China) are collected and organised into a timeline to assist analysis. It also provides some network analysis to help explore the information. If you register on their website you can browse some of their searches, but subscription for greater access is US$149/month. Business Insider gives a short overview of the company. 

Quid combs patents, company info, etc to help identify technology trends and market opportunities for paying customers.

An article in Foreign policy (Registration required) discusses the use of data analytics to look for future political events (not just elections). There are mixed views on the likelihood of success.

The Pentagon is also taking a big data approach to see if it can spot when soldiers are likely to go rogue. It can’t do that yet, and could run into legal problems if it tries to. But it may be able to improve its training regimes through such studies.

As I mentioned in an earlier blog, the Intelligence Advanced Research Projects Activity (IARPA) is trying out a range of human and computational approaches to improve intelligence analysis.

Richard Danzig has already warned [Pdf] about placing too much reliance on predictions in relation to national security. He advocates the need to focus prediction on the short term and foster preparedness for the unexpected. IARPA recognises limitations in their approach, but are seeking to reduce uncertainty about what events are predictable and which aren’t.

As Garry Kasparov pointed out for machine-assisted chess competitions, middling humans working with middling computers but with a very good process for combining the strengths of both beats powerful computers alone as well as chess grand masters using computers ineffectively. The CIA also demonstrated many years ago that more information doesn’t always make intelligence analysis more accurate, it just enhances the confidence the analyst has in their predictions.

As analytical software improves computers will hopefully play a greater role in organising and exploring data themselves and finding meaningful information for the task at hand. The value a futurist provides (for the moment at least) is in helping frame the right questions to ask of the information, being able to identify what the most relevant pieces of information may be, and going some way to addressing the “so what?” questions that arise.

It is the best of times, it is the worst of times, it is the age of wisdom, it is the age of foolishness, it is the epoch of belief, it is the epoch of incredulity, it is the season of light, it is the season of darkness, it is the spring of hope, it is the winter of despair.

Some commentators, such as Ray Kurzweil and the European Commission, think the pace of technological change is accelerating.  (as judged by time to widespread adoption). That seems true for some particular technologies, but isn’t a universal rule. Techno-optimists also believe that we are entering a golden age of technological innovation.

Others  lament that technological innovation, at least in the US, has slowed over the last 40 years. Peter Thiel has put the blame on inventors and venture capitalists for failing to think big and take greater risks. That is too sweeping; look at entrepreneurs like Elon Musk, gene sequencing technologies, and some of the clean/smart energy developments.

As the New York Times notes, predictions of technological utopia and doom are two extremes that overstate the issue. Aspects of both may eventuate.

Robert J Gordon has noted that several factors influence innovation (technological and otherwise). He identified six current “headwinds” [Pdf] that have the potential to slow it down:

• Declining birth-rates;
• Plateauing of levels of educational attainment;
• Rising inequality;
• Increasing outsourcing of a diverse range of jobs to other countries;
• The need for energy systems that are less harmful to the environment; and
• High levels of household and government debt.

Such constraints can, of course, also provide great conditions for stimulating innovation. Several of them also don’t apply to non-western countries. So rather than global stagnation, we may see a shift in hotbeds of innovation.

Declarations of slower or faster pace of change are, however, often fallacious because we don’t have good metrics for measuring meaningful technological change. You can cherry pick data to support your point of view, and since technologies don’t all move at the same speed you can point to a lack of flying cars as our technological failing, or the very rapid growth in computational power as a sign that technological progress is in an exponential growth phase.

As a former evolutionary biologist I tend to view technologies as following more of a punctuated equilibrium-style model – periods of more rapid change alternating with stages of less dramatic refinement (plateaus or equilibria) – rather than relentless and accelerating progress. Or what The Economist calls the ebbs and flows of innovation.

The Economist article notes that many of the paradigm changing inventions –fire, agriculture, electricity, automobiles, powered flight, etc. happened some time ago and many subsequent developments have just been variations on these themes. However, it also points out that technologies developed in the last few decades (such as the internet, biotechnologies and solar power) have yet to reach their full economic and societal potential.

The “scientific revolution” that began 500 years ago signaled a fundamental change in how we viewed the world. But now we seem to be entering a new phase of improving our abilities to shape the world and ourselves.

Technology adoption is not inevitable nor impervious to influence. In an article in Slate summarizing his book, Evgeny Morozov notes the need to challenge technological defeatism – the view that we can’t stop or shape how technologies are used.  He illustrates this by harking back a century to debate about noise control. [Although this seems a weak example since it is less to do with a specific technology and more about community concerns to environmental factors.]

 The Economist article noted above suggests that a critical factor governing pace of change is not technological inventiveness but the declining ability for organisations and institutions to cope with revolutionary change. Economics and market demand also come into it. The World Economic Forum has also emphasized the need to develop new ways of thinking about how to develop and use technologies.

As another Dickensian novel suggested

Train up a fig-tree in the way it should go, and when you are old sit under the shade of it.

 

The researchers behind it are interested in four questions: “How good is your memory?”,“How impulsive are you?”, “What makes you happy?” and “How much can you see?”

Cancer Research UK are also developing a game to help speed up development of better treatments for cancers. Their intent is to get the public to help analyse genetic data. So these are just part of the trend for involving the public in research that started on desktop computers many years ago with and Galaxy Zoo, but shifting to mobile devices.

These aren’t quite the full on “Gamefication” apps that I have written about previously - “mission oriented” complex games that can involve collaboration as well as competition. Nesta provides links to a range of games that attempt to address real world problems.  However, the gloss appears to be coming off the usefulness of such games, signalling the concept may have crested the maximal hype part of the hype cycle. The main criticism being that they can be poorly designed. 

It will be interesting to see which apps do generate useful research data. I’ve tried the Great Brain Experiment. It’s not as engaging or addictive as Angry Birds or Plants vs Zombies. But it does give you feedback on where your test scores sit compared with every other player, so can provide some conversational starters in the office or at parties.

Being an anonymous game means that it will be challenging for the researchers to break down the data into age and sex groupings (info they ask for at the start). How many people will answer honestly? (most probably, but what effect will a small proportion of dishonest responses have). And they can’t control for what folks have been smoking, drinking, ingesting, snorting etc. before or during the game. So not as controlled as in the lab, but more realistic of everyday life & activity.

Click here to view the embedded video.

And the company MC10 is developing temporary flexible electronic tattoos for monitoring health and physical activities. This gives a great illustration of one the directions healthcare and sport are heading.