Futuring media

2020 Media Futures is a fine example of a collaborative futuring project.  The topic is specific (Canada’s media landscape), but the practices are quite general.

2020MF uses a variety of futures methods:

  • Environmental scanning, or signals from the media future.  These are primarily news stories, arranged under general futures rubrics (Social, Technological, Economic, Ecological, Political, Values, or STEEPV) and media-specific topics (books, tv, etc).
  • Trend analysis.  2020MF determined a series of likely, powerful forces, again arrayed against STEEPV categories.
  • Driver identification, or the forces underpinning the already-selected trends and signals.  Read the full page for a good description of how they managed the group work.
  • Critical uncertainties, the powerful forces which could still appear in very different forms, unlike trends.  Note the way these are very industry-specific:

Critical uncertainties for Canadian media in 2020.

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Text analysis to anticipate genocide

HatebaseA new database project attempts to identify impending genocide by spotting key textual indicators.  It’s crowdsourced, called Hatebase, and a co-sponsor describes it like so:

Hatebase, an authoritative, multilingual, usage-based repository of structured hate speech which data-driven NGOs can use to better contextualize conversations from known conflict zones.

A fascinating idea, one part digital humanities, one part pre-crime.  It can also be localized, as a

critical concept in Hatebase is regionality: users can associate hate speech with geography, thus building a parallel dataset of “sightings” which can be monitored for frequency, localization, migration, and transformation.

(via Slashdot)

Technology’s future is S-shaped

Maybe the long boom of technological disruption will slow down, ponders sf writer Charlie Stross.

We are undeniably living through the era of the Great Acceleration; but it’s probably[*] a sigmoid curve, and we may already be past the steepest part of it. [link in original]

Ah yes, that famous S-curve.  Slow to start, fast to build, massive in effect, then ultimately tapering off, like so:

Sigmoid curve plot.

The big “S”.

So we can imagine the tide of industrial-technological change rising in the 1700s, roaring into life during the 1800s, turning into a transformational riptide through the twentieth century, and then, in the 21st, gradually… slowing… down.  The rate of innovation drops.  We become accustomed to the new.  Future shock stops shocking.

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Reversing the future

ImageJohn Crowley, brilliant writer of splendid speculative fiction, meditates on the future in the most recent Lapham’s. I’d like to draw attention to two main points, beyond the brooding lushness of Crowley’s prose.

First, there’s a futuring method on display.  Even if it’s tongue in cheek, the approach is both entertaining and potentially useful for group work.  The gist: reverse our expectations for the future.  You could even test it retrospectively:

if you simply reversed what the past had imagined, you got something close to the real existing present.

I’d like to try this on small groups.

Crowley then offers an example of this method, projecting one future:

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New Shell scenarios

Shell Oil published a set of future energy scenarios.

Two of them are older ones.  Scramble describes a global energy panic.  Blueprints assumes stronger governmental planning and control.

Two Shell scenarios in mid-stream.

Seeing how Scramble and Blueprint play out.

Shell also released two new ones:

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From the big past to the future

Ian Morris turns his huge historical scope around, and aims it at the next century.

By 2100 we will see cities with 140 million people. Robots will wage war. Humans, whose bodies have changed more in the last 100 years than in the previous 100,000 will “transcend biology.”

The futurist Ray Kurzweil calls this merger of human and machine intelligence “the Singularity.” Morris suggests that something like that may create new ways of capturing energy, communicating, thinking, fighting, working, loving, aging, and reproducing.

Unless, he says, we never get there. The paradox of development is that it produces forces that can cause catastrophe, if not managed properly. Climate change, Morris says, may be the “ultimate example.” The very fossil fuels that propelled social development upward after 1800 are now causing global warming.

But like earlier periods of climate change, Morris predicts, “this one will not directly cause collapse.” The truly scary thing is how people might react to the weather. Climate change could unleash famine, enormous migrations, disease, and perhaps even nuclear war.

Google didn’t catch the flu

Google Flu Trends getting it wrongGoogle’s flu predicting service has been impressively accurate in the past, but failed to apprehend the most recent American outbreak.

Google Flu Trends, which estimates prevalence from flu-related Internet searches, had drastically overestimated peak flu levels.

Why?

problems may be due to widespread media coverage of this year’s severe US flu season, including the declaration of a public-health emergency by New York state last month. The press reports may have triggered many flu-related searches by people who were not ill.

This may become a useful cautionary tale in our dawning age of big data.

A map of the next decade: the IFTF released a fun set of scenarios for the next ten years.

Why fun?  Because they proclaim these are all unlikely.  “too fast to be believable” is one set.  And “Type 2 scenarios depend on the conjunction of too many improbabilities”.

Decade map.

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Doom to college as we know it

One commentator looks at the San Jose MOOC decision and forecasts the fall of American higher education.

Ferenstein presents this timeline:

  1. Pilot succeeds, expands to more universities and classes
  2. Part-time faculty get laid off, more community colleges are shuttered, extracurricular college services are closed, and humanities and arts departments are dissolved for lack of enrollment (science enrollment increases–yay!?)
  3. Graduate programs dry up, once master’s and PhD students realize there are no teaching jobs. Fewer graduate students means fewer teaching assistants and, therefore, fewer classes
  4. Competency-based measures begin to find the online students perform on par with, if not better than, campus-based students. Major accredited state college systems offer fully online university degrees, then shutter more and more college campuses
  5. A few Ivy League universities begin to control most of the online content, as universities all over the world converge toward the classes that produce the highest success rates
  6. In the near future, learning on a college campus returns to its elite roots, where a much smaller percentage of students are personally mentored by research and expert faculty

A big-picture scenario

Here’s a classic scenario process, presented by Jamais Cascio.  Very useful example of the form.

Start with two drivers:

Right now, the overriding challenge facing us is the global environment, especially the climate. We’re seeing climate disruption-linked events happening faster and harder than was expected, even while the world’s moving backwards in terms of carbon controls (e.g., Canada filed the paperwork to withdraw from Kyoto in order to be able to exploit the tar sands, Germany’s carbon emissions are increasingly rapidly as they replace nuclear plants with coal, China is being China, etc.). The only place that’s seeing any real improvement is (believe it or not) the United States, and that’s because fracking is allowing us to swap natural gas in for coal. 

There’s also the state of the global economy. A mild improvement in the US as well as fear fatigue has allowed us to think that the worst is over, that everything will be okay in Europe, etc. That’s not necessarily so, and it wouldn’t really take much to tip us back into the “it’s all about to fall apart” anxiety of a year or so ago.

Next, make a continuum out of the two – nice twist: (more…)