Everything I’ve Ever Learnt About The Future

Here’s a prediction. You are reading this because you believe that it’s important to have a sense of what’s coming next.

Or perhaps you believe that since disruptive events are becoming more frequent you need more warning about potential game-changers, although at the same time you’re frustrated by the unstructured nature of futures thinking.

Foresight is usually defined as the act of seeing or looking forward – or to be in some way forewarned about future events. In the context of science, it can be interpreted as an awareness of the latest discoveries and where these may lead, while in business it’s generally connected with an ability to think through longer-term opportunities and risks be these technological, geopolitical, economic, or environmental.

But how does one use foresight? What practical tools are available for individuals to stay one step ahead and to deal with potential pivots?

The answer to this depends on your state of mind.

In short, if alongside an ability to focus on the here and now you have – or can develop – a culture that’s furiously curious, intellectually promiscuous, self-doubting, and meddlesome you are likely to be far more effective at foresight than if you doggedly stick to a single idea or worldview. This is because the future is rarely a logical extension of single ideas or conditions.

Furthermore, even when it looks as though this may be so, everything from totally unexpected events, feedback loops, behavioural change, pricing, taxation, and regulation have a habit of tripping up even the best-prepared plans.

Looking both ways

In other words, when it comes to the future most people aren’t really thinking, they are just being logical based on small sets of recent data or personal experience. The future is inherently unpredictable, but this gives us a clue as to how best to deal with it. If you accept – and how can you not – that the future is uncertain, then you must accept that there will always be numerous ways in which the future could play out. Developing a prudent, practical, pluralistic mind-set that’s not narrow, self-assured, fixated, or over-invested in any singular outcome or future is therefore a wise move.

This is similar in some respects to the scientific method, which seeks new knowledge based upon the formulation, testing, and subsequent modification of a hypothesis.

Not blindly accepting conventional wisdom, being questioning and self-critical, looking for opposing forces, seeking out disagreement and above all being open to disagreements and anomalies are all ways of ensuring agility and most of all resilience in what is becoming an increasingly febrile and inconstant world.

This is all much easier said than done, of course. Homo sapiens are a pattern seeing species and two of the things we loathe are randomness and uncertainty. We are therefore drawn to forceful personalities with apparent expertise who build narrative arcs from a subjective selection of so-called facts. Critically, such narratives can force linkages between events that are unrelated or ignore important factors.

Seeking singular drivers of change or maintaining a simple positive or negative attitude toward any new scientific, technological, economic, or political development is therefore easier than constantly looking for complex interactions or erecting a barrier of scepticism about ideas that almost everyone else appears to agree upon or accept without question.

Danger: hidden assumptions

In this context a systems approach to thinking can pay dividends. In a globalised, hyper-connected world, few things exist in isolation and one of the main reasons that long-term planning can go so spectacularly wrong is the oversimplification of complex systems and relationships.

Another major factor is assumption, especially the hidden assumptions about how industries or technologies will evolve or how individuals will behave in relation to new ideas or events. The hysteria about Peak Oil might be a case in point.  Putting to one side the natural assumption that we’ll need oil in the future, the amount of oil that’s available depends upon its price. If the price is high there’s more incentive to discover and extract more oil especially, as it turned out, shale oil.

A high oil price also fuels the search for alternative energy sources, but also incentivises behavioural change at both an individual and governmental level.  It’s not an equal and opposite reaction, but the dynamic tensions inherent within powerful forces means that balancing forces do often appear over time.

Thus, we should always think in terms of technology plus psychology, or one factor combined with others.  In this context, one should also consider wildcards. These are forces that appear out of nowhere or which blindside us because we’ve discounted their importance.

Similarly, it can often be useful to think in terms of future and past. History gives us clues about how people have behaved before and may behave again. Therefore, it’s often worth travelling backwards to explore the history of industries, products, or technologies before travelling forwards.

If hidden assumptions, the extrapolation of recent experience, and the interplay of multiple factors are three traps, cognitive biases are a fourth. The human brain is a marvellous thing, but too often tricks us into believing that something that’s personal or subjective is objective reality. For example, unless you are aware of confirmation bias it’s difficult to unmake your mind once it’s made up.

Once you have formed an idea about something – or someone – your conscious mind will seek out data to confirm your view, while your subconscious will block anything that contradicts it. This is why couples argue, why companies steadfastly refuse to evolve their strategy and why countries accidently go to war. Confirmation bias also explains why we persistently think that things we have experienced recently will continue.  Similar biases mean that we stick to strategies long after they should have been abandoned (loss aversion) or fail to see things that are hidden in plain sight (inattentional blindness).

In 2013, a study in the US called the Good Judgement Project asked 20,000 people to forecast a series of geopolitical events. One of their key findings was that an understanding of these natural biases produced better predictions. An understanding of probabilities was also shown to be of benefit as was working as part of a team where a broad range of options and opinions were discussed.

You must be aware of another bias – Group Think – in this context, but if you are aware of the power of consensus you can at least work to offset its negative aspects.

Being aware of how people relate to one another also recalls the thought that being a good forecaster doesn’t only mean being good at forecasts. Forecasts are no good unless someone is listening and is prepared to act.

Thinking about who is and who is not invested in certain outcomes – especially the status quo – can improve the odds when it comes to being heard. What you say is important, but so too is whom you speak to and how you illustrate your argument, especially in organisations that are more aligned to the world as it is than the world as it could become.

Steve Sasson, the Kodak engineer who invented the world’s first digital camera in 1975 showed his invention to Kodak’s management and their reaction allegedly was: ‘That’s cute, but don’t tell anyone.”  Eventually Kodak commissioned research, the conclusion of which was that digital photography could be disruptive.

However, it also said that Kodak would have a decade to prepare for any transition. This was all Kodak needed to hear to ignore it. It wasn’t digital photography per se that killed Kodak, but the emergence of photo-sharing and of group think that equated photography with printing, but the result was much the same.

Good forecasters are good at getting other peoples’ attention using narratives or visual representations. Just look at the power of science fiction, especially movies, versus that of white papers or power point presentations.

If the engineers at Kodak had persisted or had brought to life changing customer attitudes and behaviours using vivid storytelling – or perhaps photographs or film – things might have developed rather differently.

Find out what you don’t know.

Beyond thinking about your own thinking and thinking through whom you speak to and how you illustrate your argument, what else can you do to avoid being caught on the wrong side of history? According to Michael Laynor at Deloitte Research, strategy should begin with an assessment of what you don’t know, not with what you do. This is reminiscent of Donald Rumsfeld’s infamous ‘unknown unknowns’ speech.

“Reports that say that something hasn’t happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; we know there are some things we do not know. But there are also unknown unknowns – the ones we don’t know we don’t know….”

The language that’s used here is tortured, but it does fit with the viewpoint of several leading futurists including Paul Saffo at the Institute for the Future. Saffo has argued that one of the key goals of forecasting is to map uncertainties.

What forecasting is about is uncovering hidden patterns and unexamined assumptions, which may signal significant revenue opportunities or threats in the future.

Hence the primary aim of forecasting is not to precisely predict, but to fully identify a range of possible outcomes, which includes elements and ideas that people haven’t previously known about, taken seriously or fully considered.

The most useful starter question in this context is: ‘What’s next?’ but forecasters must not stop there. They must also ask: ‘So what?’ and consider the full range of ‘What if?’

Consider the improbable

A key point here is to distinguish between what’s probable, and what’s possible. (See Introducing the 4Ps post).

Sherlock Holmes said that: “Once you eliminate the impossible, whatever remains, no matter how improbable, must be the truth.” This statement is applicable to forecasting because it is important to understand that improbability does not imply impossibility. Most scenarios about the future consider an expected or probable future and then move on to include other possible futures. But unless improbable futures are also considered significant opportunities or vulnerabilities will remain unseen.

This is all potentially moving us into the territory of risks rather than foresight, but both are connected. Foresight can be used to identify commercial opportunities, but it is equally applicable to due diligence or the hedging of risk. Unfortunately, this thought is lost on many corporations and governments who shy away from such long-term thinking or assume that new developments will follow a simple straight line.  What invariably happens though is that change tends to follow an S Curve and developments tend to change direction when counterforces inevitably emerge.

Knowing precisely when a trend will bend is almost impossible but keeping in mind that many will is itself useful knowledge.

The Hype Cycle developed by Gartner Research is also helpful in this respect because it helps us to separate recent developments or fads (the noise) from deeper or longer-term forces (the signal). The Gartner model links to another important point too, which is that because we often fail to see broad context, we tend to simplify.

This means that we ignore market inertia and consequently overestimate or hype the importance of events in the shorter term, whilst simultaneously underestimating their importance over much longer timespans.

An example of this tendency is the home computer. In the 1980s, most industry observers were forecasting a Personal Computer in every home. They were right, but this took much longer than expected and, more importantly, we are not using our home computers for word processing or to view CDs as predicted. Instead, we are carrying mobile computers everywhere, which is driving universal connectivity, the Internet of Things, smart sensors, big data, predictive analytics, which are in turn changing our homes, our cities, our minds and much else besides.

Drilling down into the bedrock to reveal the real why.

What else can you do to see the future early? One trick is to ask what’s behind recent developments. What are the deep technological, regulatory of behavioural drivers of change? But don’t stop there.

Dig down beyond the shifting sands of popular trends to uncover the hidden bedrock upon which new developments are being built. Then balance this out against the degree of associated uncertainty.

Other tips might include travelling to parts of the world that are in some way ahead technologically or socially. If you wish to study the trajectory of ageing, for instance, Japan is a good place to start. This is because Japan is the fastest ageing country on earth and consequently has been curious about robotics longer than most. Japan is already running out of humans and is looking to use robots to replace people in various roles ranging from kindergartens to aged care.

You can just read about such things, of course. New Scientist, Scientific American, MIT Technology Review, The Economist Technology Quarterly are all ways to reduce your travel budget, but seeing things with your own eyes tends to be more effective. Speaking with early adopters (often, but not exclusively younger people) is useful too as is spending time with heavy or highly enthusiastic users of products and services.  

Academia is a useful laboratory for futures thinking too, as are the writings of some science fiction authors. And, of course, these two worlds can collide. It is perhaps no coincidence that the sci-fi author HG Wells studied science or that many of the most successful sci-fi writers, such as Isaac Asimov and Arthur C. Clarke, have scientific backgrounds.

So, find out what’s going on within certain academic institutions, especially those focussed on science and technology, and familiarise yourself with the themes the best science-fiction writers are speculating about.

Will doing any or all these things allow you to see the future in any truly useful sense? The answer to this depends upon what it is that you are trying to achieve. If you aim is to get the future 100% correct, then you’ll be 100% disappointed. However, if you aim is to highlight possible directions and discuss potential drivers of change there’s a very good chance that you won’t be 100% wrong. Thinking about the distant future is inherently problematic, but if you spend enough time doing so it will almost certainly beat not thinking about the future at all.

Creating the time to peer at the distant horizon can result in something far more valuable than prediction too. Our inclination to relate discussions about the future to the present means that the more time we spend thinking about future the more we will think about whether what we are doing right now is correct. Perhaps this is the true value of forecasting: It allows us to see the present with greater clarity and precision.

Richard Watson April 2023. richard@nowandnext.com

How to spot ‘weak signals’

One of the biggest problems with the current digital deluge is the tendency to no longer see what’s directly in front of us. The sheer amount of information now being passed around means that we’re becoming less able to filter what’s really important from what’s really not. Information is no longer power. Our deep and undivided attention is.

Constant digital distraction (which results in constant partial attention) also means that our concentration spans are shortening (or so they say) and our peripheral vision is narrowing. Throw in some headphones and things aren’t looking good, especially if you are seeking new opportunities or risks. This is because the early harbingers of forthcoming upheaval and disruption are often hidden in tiny snippets of seemingly trivial information or obscured in plain sight in the shadows and auditory obfuscations of our everyday existence.

So how can you spot these ‘weak signals’ or other forerunners of change? How can you spot things that don’t tend to announce themselves in huge data sets? How can you mine for insights in research groups when you don’t know exactly what you are looking for?

The answer is to develop a mind-set that’s always looking for these things. You need to become more attuned to instinct and gut feelings. You need to become furiously curious. You need constantly look for things that are new and might represent a shift in how things are seen or done. But to do this you need to unfreeze and then re-set your mind-set towards deep looking and deep listening.

You also need to go to where anomalies initially emerge, which tends to mean the edges or fringes of established markets and thinking. This might be young minds or it could be academic institutions or upstart start-ups. It might even be passionate users of particular products and services (‘super-users’) or particular places where being different or quirky is seen as being culturally useful or prestigious (California not North Dakota, although the urban fringes of Fargo might contain something, or someone, of interest).

Or you can be lazy. Cultural change often procedes technological or regularly change, so become attuned to new currents in advertising, music and film. For example, I heard the lyric “Don’t go digital on me” in a song lyric the other day. Is that significant? Or there’s an ad on TV for a chocolate bar with the slogan “undivide your attention.” Again, significant?

Beyond anecdotes like these it’s rather difficult to be precise. After all, how can one explain what one’s looking for when one doesn’t really know what one is looking for and whatever it that you are looking for keeps changing the whole time? I think the answer to this is to accept that you will never fully know and to keep looking regardless.

This isn’t something that’s ad hoc. You cannot create a ‘search party’ that looks for weak signals for a week and is then disbanded. It’s something that’s continuous and the activity will suit some personality types more than others.

Let me give you a few more examples. I was in Brooklyn, New York, recently. I was in a hotel lift and someone (I’m assuming not a graffiti artist) had written “Lonely together” in huge white letters on the glass panel inside the elevator. Why was it there? What did it mean? It could have been a subliminal ad for a TV show of the same name or perhaps it meant something more?

Or how about a few years ago when Google bought Zagat, the publisher of local restaurant guides (published on paper). This made no sense. Why would an online publisher (sorry, tech company) buy someone that puts ink on dead trees? Could it be that they were interested in local expertise or search or did they see a role for paper in a digital world? (come to think of it, why did Google send me summaries of my Google Adwords campaign in a posted letter – on paper?). Question anything that doesn’t make sense or doesn’t fit an established pattern. To invert a popular schooldays phrase: question every answer.

Of course, if you start frequenting the fringes you will inevitably bump into some fairly fringe people. Some will be weird, quite possibly annoying and probably of no use whatsoever. But don’t judge these people too soon. Maybe they aren’t crazy. Maybe they are right, but just a little bit early. What’s thought of as weird, crazy or just plain impossible one moment has a habit of becoming conventional wisdom over time. So, button your lip and keep your mainstream prejudices and cynicism to yourself. For example, there are ‘tech hermits’ living off-grid in rural North America. Some of these people claim that the use of mobile phones and Wi-Fi has made them sick. I had a boss once that carried a business card that read “Maybe they’re right” printed on the reverse. Maybe he was right.

This is the opened minded mind-set you’re after and it’s a mind-set that can equally be applied to reading newspapers, looking at webpages or talking to strangers on the subway. (Do you do that? Why not? Expand your network and experiences). Keep asking yourself why someone is saying something? What’s behind a story or opinion? What do they want? What’s their interest here? Are they alone in thinking or doing this?

Also, be aware that you (and everyone else) sees the world and everything in it through a lens hand-crafted from personal experience. What you need are interchangeable lenses. You need one that’s for narrow close ups and another for wide big picture panoramas.

And be aware that you will suffer from a number of notable cognitive biases too, most significantly confirmation bias. These biases seek to close our minds by persuading us (usually subconsciously) that what we are seeing aligns with things we’ve already seen or things we already think or believe. In other words, we tend to frame things in a particular way based upon what we’ve experienced before. You need to be aware of this and fight against it if you are to discover anything that vaguely resembles objective reality.

A more recent example of a weak signal. Why are twenty-somethings buying old tech? For example, what’s behind the re-birth of vinyl and why are so many people, including smart people that work in Silicon Valley and for MI5 (allegedly), using what might be called dumb-phones over smart- phones? Are the two things possibly connected? You can figure this one out yourself, but you might need to switch your smart-phone off to do this.

One final thought. Liberate yourself from the false precision of numbers. Weak signals are, by definition, weak. They are fuzzy, unclear and indistinct. They represent small numbers of people (sometimes just one person) bravely thinking about the world in a different way or doing things somewhat differently from almost everyone else. You cannot put meaningful numbers around these people to ‘prove’ that they are significant. If you can prove it it’s a trend (or possibly a fad or counter-trend) it no-longer represents a weak signal. Got it?

References:
Paul J.H . Shoemaker and George S. Day, ‘Making sense of weak signals’, MIT Sloan Management Review, Spring 2009,
Paul J.H. Shoemaker and George S. Day, ‘Scanning the Periphery’, Harvard Business Review, November 2005.
Martin Harrysson, Estelle Metayer and Hugo Sarrazin, ‘The strength of weak signals’, McKinsey Quarterly, February 2014.

新兴科技时间轴(2014——2030+)

Screen shot 2014-07-07 at 16.41.20

 

这是和帝国理工大学技术预测同行们(尤其是阿莱克斯·阿亚德(Alex Ayad),但是在后期也要特别感谢克里斯·哈利(Chris Haley))共同创作的新型科学和技术时间轴。上面是图表完工时的图片。我们对于是否把“移动电话数量超过人口”列为“当下”讨论了很久,但是电话用户超过69亿人,已经很接近人口总数了。
请点击本段最后的链接,下载适合打印的高分辨率PDF版本(建议用彩色A3或更大纸张打印)。在一周左右时间内,将会有图表的纸质打印版。在本博文底部是一些展示该图表是如何创建的图片,以及图表是如何演进的。新兴科技-5

至于图表上有什么,有5个关键大技术:数字技术(主要是信息技术)、生物技术、纳米技术、神经技术和绿色技术(有时被称为清洁技术)。

我们把图表分成3个时间区域。第一个区域是“当下”,我们定义为现在或附近(2014-2015),同时至少1000个实际例子(事件可能是一次性出现的事,但是创新一般至少要有1000个实际例子才会纳入表中)。“很有可能”是第二个区域,被定义为2015-2030。第三个区域是“有可能”,被定义为从2030年往后可能出现的事。图表的绝大部分都是严肃的,但是我们没能抗拒在一些区域娱乐一下的冲动
希望你们都喜欢它,如果你觉得它有意思或者有用的话,请和他人分享。请注意本时间轴的出版是基于知识共享许可的,所以你可以在未询问情况下将其用于商业目的或者制作不同版本。但是如果使用时能链接回我们的初始版本,我们将感激不尽。
至于每条线上有什么,这里是清单:
绿色技术 当下
廉价太阳能聚集器
绝缘气凝胶建筑
振动能量采集
社区电网
能回应指令的家用电器
LED路灯
电网规模贮存
家庭电厂(冷热电联供系统)
智能仪表
藻类生质燃料
绿色技术 很有可能
超级电容车
消费者即时定价
100%淘汰白炽灯
氢的人工光合作用
合成飞机燃料
周围的射频能量采集
束能量用于生态监测和军事无人机
大规模的碳捕捉和碳贮存
摩天大楼上的透明(有机)太阳能电池
生物可降解电池
自主车辆专用车道
电动车辆路上感应充电
超市合成肉
绿色技术 有可能
行波反应堆
燃料电池驱动的轻型客机
无人机运送比萨
商业海洋热能转换
微型风能水能收集建筑外墙
汽车波转子发动机
钍反应堆
给海洋施以铁质肥料
用3D打印技术生产的适用于垂直农业的土壤
高速人行道
昆虫汉堡食物车
超回路大众运输系统
用托卡马克核聚变发电
卫星束太空太阳能
生物技术 当下
DNA时间确认机构
基因疗法
合成有机物
对于先天性疾病进行基因测试
入侵身体以增强感官
用3D打印技术生产的骨科植入物
商业宠物克隆
源于作物的朔料
基于基因的主动医学介入
为制药培育人源化的动物
生物技术 很有可能
预防性抗生素禁止用于动物
个性化的微生物疗法
无处不在的生物感应
非源于动物的皮革
非处方基因测试
对帕金森氏综合征进行干细胞治疗
用3D打印技术生产的生物纳米支架
人类器官克隆
为个人数据存储嵌入射频识别技术
发现最后的抗生素
生物技术 有可能
用纳米纤维制造人造肌肉
基于DNA的数据贮存
微生物感应的食品包装
引入转基因蚊子以消除疟疾
人类基因工程合法化
纹身电路(人体上的视频纹身)
克隆人类
合成有机物所带来流行病
数字技术 当下
移动电话数量超过人口 (情况转变则不属于这一类?)
生活记录
加密货币
连接到网络的牙刷
现实增强眼镜
预防犯罪算法
NFC指甲
可扫描条码的墓碑
能面部识别的中央摄像头
阿凡达女友
用于游戏的大脑-计算机基本界面
跨洲机器人手术
数字技术 很有可能
实时语言翻译
量子计算机用于解密
分析内衣
AI用于全科医生手术
无辅助机器人手术
物联网超过500亿个设备
能读唇语的中央摄像头
网络攻击导致整个城市范围内断电
不用电池的无线沟通
自主电子出租车车队
实体信用卡过时
触觉学衣服
情绪感知器
昆虫大小的侦查机器人
全息数据存储
AI用于无人机-无人机战斗
太阳耀斑消除GPS网络
数字技术 可能
侵入已经植入的神经设备
城市禁止人类驾驶员
预测战争的算法
商业飞机由智能手机劫持
战事与游戏合并
机器人数量超过人类
物联网超过1万亿个设备
终身阿凡达助手
记录人类从出生到死亡整个生命
家用冰箱感知保质期
完全自主的战场机器人
量子电脑用于材料设计
纳米技术 当下
用于衣物的抗病毒纳米粒子
化妆品和遮光剂中的纳米粒子
朔料打印的电子电路
量子点电视
癌症成像和治疗的纳米粒子
用于培育人体部位干细胞的支架
蛋白质结晶的模板
自我修复的漆点和表面
用于合成神经元和合成神经植入物的纳米管
消费者电子产品中的甲醇燃料电池
纳米技术 很有可能
人工电磁材料天线
可碾压的屏幕和设备
纳米技术 可能
实验室演示人工电磁材料隐身
旋光仪使计算接近光速
室温超导体
量子点夜视窗
自主数据密集
生态系统单层石墨超级电容自我复制
IBM用动画原子做成动画片
全朔料的晶体管
下一代超轻型合成材料
每比特数据有100个原子密集
神经技术 当下
耳蜗植入
大脑指纹用于法庭
益智药用于医学或休闲使用
由思维控制的假肢
活跃大脑区域的神经成像
神经技术 很有可能
思维控制的轮椅
手机对眼球移动追踪
解码意向的算法
适应性电子助手避免信息超负荷
人工视网膜植入
不会宿醉的酒精替代品
神经技术 可能
侵入植入的神经设备
大脑-电脑界面广泛补充了键盘使用
空中旅行者大脑指纹常规
通过fMRI对梦成像和记录
沟通设备广泛嵌入到人体
基本想法的人工神经编写
用大脑假体提升或消除记忆
终结痴呆

设计开发
设计大体上基于我之前2010年后趋势和技术时间轴做的 (需要PDF版本请点击这里)。第一个草图是在厨房桌子上用铅笔在A3白纸上画的,之后不断改进了好多版(记得大约是十二版)。圆圈最初是用厨房盘子和大碗画的,彩色的线最初是用荧光笔和我孩子们的马克笔混合创作的。专业设计之前的最终版本画在了A3绘图纸上,使各要点契合并连接好。设计的功劳也属于劳伦斯·怀特利(Lawrence Whitely),特别感谢帝国理工大学的科林(Kereen)。

关于未来的更新,我们已经在考虑动画版以及积极和消极版本(乌托邦版和非乌托邦版)。如果关于图表的未来更新版本,您觉得哪些事该/不该出现在图表上(或是看到一些愚蠢的错误,请务必告之我们)。

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The Future of National Libraries

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Ellen at the State Library of NSW has sent me a link to a paper from the National Library of Scotland (NLS) that considers the influences that will shape the development of the NLS over the next 20 years. I really should be reading a modernisation review of public libraries from the Department for Culture, Media and Sport (UK) sent to me by Andrew in England, but somehow this paper caught my eye. As a result I printed out all 85 pages and started reading it on a long train journey last night. Here’s my take on the report.

First of all it is important to note that this is a think piece is about national libraries, which is not wholly the same as either research libraries or public libraries although the overlap is considerable. It is also a linear futures thinking piece as opposed to a more multi-polar scenarios document.

First of all their key drivers of change:

1. Changing patterns of publishing
2. Shifting customer needs and behaviour
3. New competition
4. The political environment
5. Internal organisational issues

The paper looks at each of these drivers and considers likely impact. Interesting, both sustainability and digitalisation were considered as givens and it is made clear that the responsibility for digital literacy lies with the education sector not national libraries.

I partly agree with this last point and on balance I also agree that digitalisation should be a theme running throughout all the thinking. However, I also believe that they might be missing something. If you were to look at the future of national libraries from a scenarios perspective you would have one scenario where the thinking around sustainability and digitalisation is turned on its head. Anyway, here’s what they say (my words) about demographics (shifting customer needs), competition, government and internal issues.

Demographics

Declining number of younger users
Rising number of older people, especially very old people (e.g. number of over 75s in Scotland are expected to rise by 81% by 2031). This means that even by 2030 there will be significant numbers of digital immigrants around, many of whom will still prefer paper formats.
Booming interest in family history (partly, I assume, due to ageing and globalisation)
Greater diversity in terms of student types
Younger users seeing “little need or desire to visit the physical library” (I’ll come back to this point at the end).

Competition

Commercial information suppliers will continue to compete with NLS
Connectivity and digitalisation mean increased opportunities for collaboration. Likely mergers between institutions and organisations in the ‘cultural resources’ or ‘memory institutions’ space (i.e. libraries, art galleries, museums, film archives, sound archives etc). This will be driven largely by the digitalisation of materials, which will lead to an ever-greater integration of the content owing institutions themselves. I think this is a very important point. We will experience a blurring between what art galleries, museums and libraries do or represent and national libraries will shift from collecting books to collecting all kinds of items relating to cultural and intellectual heritage.

Government

We should assume that governments will continue to seek cost savings and this will force libraries to develop new income streams. This will also lead to the development of more paid-for services. This is unlikely to result in a total paradigm shift from free to fee but there will be a significant move towards payment for premium services. The rise of e-books and online information will also drive the trend towards hybrid charging models because of the easy availability of mobile and online micro- payments.

Internal organisational issues

A big issue is recruiting younger people into the profession, although it seems to me that the idea of professional librarianship will slowly fade away. The model of the future will be around information professionals and this will encompass a variety of skills ranging from IT and fundraising to management, marketing and even early years education and aged-care specialists.

Other points of interest

Libraries will shift from passive collators to active co-creators of information. Customers will demand more personalisation around ‘their’ information.There will be more do-it-yourself and self-service options. There will be greater automation due to the explosion of content national libraries can no longer collect everything — the shift will be towards selection or edited collections.

OK, so what has the paper missed?

First of all there seems to be little or no discussion of the physical space. Indeed, one author says: “:it becomes increasingly unlikely that users will ever visit the physical premises and they will increasingly have an expectation that services will be delivered directly to their devices wherever they are.” True. This will happen. But some people will still value the physical space in much the same way that some people will still value paper over pixels.

Another issue that is not really discussed relates to information trust. If there is an explosion of content one of the consequences is a declining level of quality. If people have shorter attention spans and information quality is declining them surely what some people will need is someone to talk to whom they trust. Technology can do this up to a point but I think people in combination with technology do it much better.
And this leads me onto my final point, which is that the authors are following the technology ahead of the psychology. Libraries are not just about books. They are also about people.

Read the whole paper yourself here:

http://www.nls.uk/about/policy/docs/future-national-libraries.pdf