Posts Tagged ‘forecast’
“The press is a blind old cat yelling on a treadmill”*…
Well, in any case, it’s been a trying time for journalism. What’s next? The estimable Nieman Lab polled 21 experts…
Each year, we ask some of the smartest people in journalism and media what they think is coming in the next 12 months. At the end of a trying 2024, here’s what they had to say…
They’re all eminently worth reviewing, but your correspondent would call out a few:
Nick Petrie: “The year newsrooms tackle their structural issues“
Many publishers remain anchored to hierarchies born in the print era, with editorial at the center and product and technology bolted on as afterthoughts…
Ben Smith: “Back to the Bundle“
If media companies can’t figure out how to be the bundlers, other layers of the ecosystem — telecoms, devices, social platforms — will…
Alice Marwick: “The mainstream media will lose its last grip on relevancy“
The gap between mainstream media readers, people who get most of their news through influencers or partisan social media, and people who barely think about news at all will create a fundamental schism in how Americans see the world… 2024 was the year “disinformation” outlasted its usefulness. Moving forward, we should not be concerned with isolated incorrect facts, but with the deeply-rooted stories that circulate at all levels of culture and shape our points of view. The challenge for 2025 is to confront these deeper epistemic divides that shape how Americans understand the world…
And on a more positive (albeit, more distant) note, Adam Thomas: “Impact investment enters the chat“
Somewhere in the future, beyond 2025, a flourishing landscape of adequately financed, equitable media enterprises will deliver impactful content, serve diverse communities, and achieve financial independence…
These and the other provocative pieces at “Predictions for Journalism, 2025,” from @niemanlab.org.
(Image above: source)
* Ben Hecht (from Erik Dorn, his first novel, written while he was a journalist covering the aftermath of World War I in Berlin for the Chicago Daily News)
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As we contemplate civil discourse, we might recall that it was on this date in 1768 that the first volume of the first edition of the Encyclopædia Britannica was published by its Edinburgh-based founders, Colin Macfarquhar and Andrew Bell. It relatively quickly attained a reputation for excellence in its summarization of knowledge. It prospered in print until the digital revolution and the advent of, first Encarta (which decimated print encyclopedia sales), then Wikipedia (which has much broader and often deeper coverage than a print encyclopedia can, and which has continued to improve its reliability to a level approaching that of EB).
“The function of economic forecasting is to make astrology look respectable.”*…
For as long as there have been markets, there have been those who forecast them. Bob Seawright explains why, for all of that “practice,” forecasting is never– and never can be– a precise nor “perfect” pursuit…
… On our best days, wearing the right sort of spectacles, squinting and tilting our heads just so, we can be observant, efficient, loyal, assertive truth-tellers. However, on most days, all too much of the time, we’re delusional, lazy, partisan, arrogant confabulators. It’s an unfortunate reality, but reality nonetheless.
But that’s hardly the whole story.
We are our own worst enemy, but there are other enemies, too. Despite our best efforts to make it predicable and manageable, and even if we were great forecasters, the world is too immensely complex, chaotic, and chance-ridden for us to do it well…
Eminently worth reading in full for Seawright’s accounts of human nature, complexity, chaos, and chance– and of the ways in which they make confident predictions of the future a “Fool’s Errand.”
As Niels Bohr once said (paraphrasing a Danish proverb), “it is difficult to make predictions, especially about the future.”
(Image above: source)
* John Kenneth Galbraith
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As we seek clarity, not certainty, we might recall that it was on this date in 1983 that Thomas Dolby’s “She Blinded Me with Science” reached #5 on the Billboard Hot 100 chart.
“Prediction is very difficult, especially if it’s about the future”*…
But, as Dylan Matthews reports, some are better at it than others…
The question before a group made up of some of the best forecasters of world events: What are the odds that China will control at least half of Taiwan’s territory by 2030?
Everyone on the chat gives their answer, and in each case it’s a number. Chinmay Ingalagavi, an economics fellow at Yale, says 8 percent. Nuño Sempere, the 25-year-old Spanish independent researcher and consultant leading our session, agrees. Greg Justice, an MBA student at the University of Chicago, pegs it at 17 percent. Lisa Murillo, who holds a PhD in neuroscience, says 15-20 percent. One member of the group, who asked not to be named in this context because they have family in China who could be targeted by the government there, posits the highest figure: 24 percent.
Sempere asks me for my number. Based on a quick analysis of past military clashes between the countries, I came up with 5 percent. That might not seem too far away from the others, but it feels embarrassingly low in this context. Why am I so out of step?
This is a meeting of Samotsvety. The name comes from a 50-year-old Soviet rock band — more on that later — but the modern Samotsvety specializes in predicting the future. And they are very, very good at it. At Infer, a major forecasting platform operated by Rand, the four most accurate forecasters in the site’s history are all members of Samotsvety, and there is a wide gap between them and fifth place. In fact, the gap between them and fifth place is bigger than between fifth and 10th places. They’re waaaaay out ahead.
While Samotsvety members converse on Slack regularly, the Saturday meetings are the heart of the group, and I was sitting in to get a sense of why, exactly, the group was so good. What were these folks doing differently that made them able to see the future when the rest of us can’t?…
The “secrets” of superforecasters: “How a ragtag band of internet friends became the best at forecasting world events,” from @dylanmatt in @voxdotcom.
(Image above: source)
* Niels Bohr
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As we contemplate change, we might recall that it was on this date in 1781 that William Herschel discovered Uranus. The first planet to be discovered with the aid of a telescope, he initially thought that it was a comet.
And on this date in 1930, Clyde Tombaugh discovered Pluto. Originally designated the ninth planet, it has been “demoted” to minor (or dwarf) planet status.
“They laughed at Columbus and they laughed at the Wright brothers. But they also laughed at Bozo the Clown.”*…
Most technologies that grow up to be important, Benedict Evans observes, start out looking like toys with little or no practical application.
Some of the most important things of the last 100 years or so looked like this. Aircraft, cars, telephones, mobile phones and personal computers were all dismissed as toys. “Well done Mr Wright – you flew over a few sand dunes. Why do we care?”
But on the other hand, plenty of things that looked like useless toys never did become anything more than that. The fact that people laughed at X and X then started working does not tell us that if people now laugh Y or Z, those will work too.
So, we have a pair of equal and opposite fallacies. There is no predictive value in saying ‘that doesn’t work’ or ‘that looks like a toy’, and there is also no predictive value in saying ‘people always say that.’ As [Wolfgang] Pauli put it, statements like this are ‘not even wrong’ – they give no insight into what will happen.
Instead, you have to go one level further. You need a theory for why this will get better, or why it won’t, and for why people will change their behaviour, or for why they won’t…
That’s to say, Evans suggests, you need to be able to envision a roadmap from “toy” to wide, practical use…
These roadmaps can come in steps. It took quite a few steps to get from the [Wright Flier, pictured above left] to something that made ocean liners obsolete, and each of those steps were useful. The PC also came in steps – from hobbyists to spreadsheets to web browsers. The same thing for mobile – we went from expensive analogue phones for a few people to cheap GSM phones for billions of people to smartphones that changed what mobile meant. But there was always a path. The Apple 1, Netscape and the iPhone all looked like impractical toys that ‘couldn’t be used for real work’, but there were obvious roadmaps to change that – not necessarily all the way to the future, but certainly to a useful next step.
Equally, sometimes the roadmap is ‘forget about this for 20 years’. The Newton or the IBM Simon were just too early, as was the first wave of VR in the 80s and 90s. You could have said, deterministically, that Moore’s Law would make VR or pocket computers useful at some point, so there was notionally a roadmap, but the roadmap told you to work on something else. This is different to the Rocket Belt [pictured above right], where there was no foreseeable future development that would make it work…
Much the same sort of questions apply to the other side of the problem – even if this did get very cheap and very good, who would use it? You can’t do a waterfall chart of an engineering roadmap here, but you can again ask questions – what would have to change? Are you proposing a change in human nature, or a different way of expressing it? What’s your theory of why things will change or why they won’t?
The thread through all of this is that we don’t know what will happen, but we do know what could happen – we don’t know the answer, but we can at least ask useful questions. The key challenge to any assertion about what will happen, I think, is to ask ‘well, what would have to change?’ Could this happen, and if it did, would it work? We’re always going to be wrong sometimes, but we can try to be wrong for the right reasons…
A practical approach to technology forecasting: “Not even wrong: predicting tech,” from @benedictevans.
* Carl Sagan
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As we ponder prospects, we might send carefully-calculated birthday greetings to J. Presper Eckert; he was born on this date in 1919. An electrical engineer, he co-designed (with John Mauchly) the first general purpose computer, the ENIAC (see here and here) for the U.S. Army’s Ballistic Research Laboratory. He and Mauchy went on to found the Eckert–Mauchly Computer Corporation, at which they designed and built the first commercial computer in the U.S., the UNIVAC.
“Memories, you’re talking about memories”*…
It’s natural, here at the lip of a new year, to wonder what 2019 might hold. And it’s bracing to note that Blade Runner (released in 1982) is one of 14 films set in a future that is this, the year on which we’re embarking.
But lest we dwell on the dark prognostication they tend to portray, we might take heart from Jill Lepore’s wonderfully-entertaining review of predictions: “What 2018 looked like fifty years ago” and recent honoree Isaac Asimov’s 1983 response to the Toronto Star‘s request for a look at the world of 2019.
Niels Bohr was surely right when he observed that “prediction is difficult, especially about the future.”
* Rick Deckard (Harrison Ford), Blade Runner
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As we contend with the contemporary, we might spend a memorial moment honoring two extraordinary explorers who died on this date. Marco Polo, whose coda to his remarkable travelogue was “I did not tell half of what I saw,” passed away on this date in 1324.
And Galileo Galilei, the Italian physicist, philosopher, and pioneering astronomer, rose to his beloved heavens on this date in 1642. Galileo (whom, readers will recall, had his share of trouble with authorities displeased with his challenge to Aristotelean cosmology), died insisting “still, it [the Earth] moves.”
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