Monday, September 26. 2016
DataSwarm system chart of the US Election meme swarm
(Update - we wrote this before the TV debate, we make a few comments about what we see in the last 12 hours or so since the election at the end)
I guess like quite a few Data Analytics/Insights companies, we've been tracking the US election using our systems (more details on our DataSwarm system here) just to see what it is telling us vs what we can see in the press etc, and vs. what others are saying.
Anyway, one of the predictors we follow closely is Nate Silver, as his 5-38 operation has called quite a few elections accurately before. Like many others, he is tracking the rise of Trump from what was considered a low (c 13.6% chance of election) just after the Democrat National Convention, and a steady rise since then till now they are about neck and neck (see their time chart here, just below the breakline.)
This (and similar) is interesting to us, as our system has only ever seen Trump out in front from the get go, the only thing that has varied is how far. To be sure this is because we are looking at different factors, we are looking at the memetic impact of Trump vs Clinton, not poll data, and Trump has never flagged in the meme race.
A quick refresher on Memetics - the term meme was coined by Richard Dawkins as a "mental gene", and its role is to replicate itself by colonising other minds. Like genes, memes travel in groups called "memeplexes", and the ones that are prevalent in a culture or subsector are what we term the "zeitgeist". There is a branch of mathematics called Memetic Analysis which is quite useful for analysing this, its a sort of cross breed between the maths of Viruses spreading and feedback-loop System Dynamics. Anyway, the chart above shows the output of what we call "zeitgeist tracking", that presents as a "data swarm" (especially as it moves over time) of the relative position of relevant memes to a topic (in this case the US Election), here shown on on two quite useful axes:
Also shown are 2 other blobs of memes - on the Y axis are relevant ones that haven't yet gained much traction (the Darwinian Stew of memes in the culture waiting to find believers - Terry Pratchett's Small Gods describes this issue perfectly) and on the X axis, memes that are second order - they are part of the memeplex but not highly relevant to the topic under examination (nonetheless, they can be useful for splitting out sub-tribes)
We also tracked the primaries at the time, and Trump moved off ahead of all the Republican hopefuls wit gathering pace, and never looked back. That allowed us useful data to to calibrate the memetic algorithms and now we want to see what they predict for the US Election outcome. We have been tracking the US Elections since the Republican Caucus, and Trump has always been in front, even during the Democrat National Convention. If the lessons of the Primaries hold true, he will win - not by much, but he will win, right now our system says he holds the dominant Zeitgeist and the rate of change is not slowing vs a vis Clinton.
Of course things can still go totally wrong, and tonight's Candidate's Debate may be just that, as in memetic terms the debate will be throwing around a number of highly relevant memes via a medium that has a potentially huge Influence. We are quite looking forward to seeing how it pans out memetically!
(Update - 12 hours on, we see no sign at all that Clinton has made any discernable difference in relative positioning yet. It's probably too early to see enough data to be clear until US has had a full day to talk about it, so by tomorrow morning (28 September) UK time.. The mainstream media pundits are already saying she won, but as far as we can see the data is saying it was too close to make any difference to the big picture. The risk for Clinton is that (if Brexit is anything to go by) the MSM tend to suffer from confirmation bias and readily believe their own agendas)
The essential Caveats
To be sure, this approach is far from foolproof but we are curious to see what it can do. The major pitfalls are:
Firstly, the General Election is somewhat more complex terrain than the standard fare of our system (customer service optimisation, consumer insight, brand messaging, influencer identification etc etc) as the nature of political constituencies give the ecosystem a series "break points" - ie a 55% / 45% advantage for the winning candidate can still result in then losing, due to uneven spraed of support - ie a minority of "over-won" states and a majority of "just-lost" states. And to make it more interesting, the states are not the same size. But this didn't impact the primaries that much (however, that may have been because by the time of voting nearly all the other Republican candidates' share of the meme-space had become relatively insignificant).
Secondly, the Zeitgeist is a measure of the recordable transmission of an idea and we know from following UK elections that people tend to publically talk politically acceptable and privately vote in their own interest, but Trump (in general) is the non-acceptable face so those showing positive interest in him are probably under, not over represented in the public discourse. We do track Zeitgeist sentiment, and pro Trump sentiment is on average lower than pro Clinton, but not hugely so (see above note re acceptable), as neither are particularly popular (or more accurately, both are highly polarised) but strictly speaking meme transmission is Wildean in our experience - what is more important is the scale of the conversation.
Friday, September 9. 2016
....is that they do things like this - Grauniad:
They also banned the poster of the photo when he complained. The photograph was the one above. You may remember it as iconic of the Vietnam era, and it turned opinion against the war globally. Problem is the Facbook algorithms don't like it, nor did the algorithm's handlers as:
"it is difficult to create a distinction between allowing a photograph of a nude child in one instance and not others".
Anyway, after fairly worldwide complaint, criticism and derision, they have reinstated that single photograph because even though its usually considered nakedness and child porn etc, in this case "the value of the photograph outweighs the value of protecting the community".
There is a certain irony in that, probably completeley missed by the Facebook PR team. But it points to the underlying problem, I suspect, that due to a combination of age, education (all tech) and arrogance (who needs to know anything except tech) a large number of Facebook employees* didn't (still don't?) have a clue about why it is important.
The limitation of curation-by-algorithms has been cruelly exposed in all its over-simplicity.
The scary thing is that Facebook is now the world's largest de facto publisher, and the most profitable. If this (and their propensity for political censorship) is the future, it will truly Change the World - but probably not in a good way.
I feel it is almost the responsibilty of the Rest of Humanity to start bombarding Facebook with images and stories that upset their algorithms but are important. Starting with Renoir.....
* Evens money on "the intern is to blame" tomorrow, anyone?
Friday, September 2. 2016
Gartner diagram of the future Digital Workplace
From the Deflating Bubbletime Dept:
A few days ago I read the takedown of Gartner's view on Robotics in Horses for Sources, essentially it was a fisk of Gartner's current trendency to make fairly lurid predictions about our Digital Future - they have predicted that by 2018, more than three million workers globally will be supervised by "robo-bosses" and that one in three jobs will be converted to software, robots and smart machines by 2025, for example.
It's not just Robotics - reading their thoughts on the Top 10 Technologies Driving the Digital Workplace my initial thought was it was a well needed piss-take on the current Digital Everything trope (see the diagram above) but reading the article I realised they were deadly serious. I'm not going to summarise it here, the link above goes to the article if you are interested. Our view is that the actual technologies of the Digital Workplace will look like the diagram above, rather than their dreams of Office Automation 1.0, for quite some time.
No, the real question I'm asking is similar to the one the article on the robotic analysis asked:
So why, pray tell, is Gartner, a respected voice in IT research, continually pounding us with continual scaremongering that we're all doomed to the will of the robot
Similarly, why are there such clearly overblown claims for "Office Automation". What's going on here? These guys are supposed to be analysts, not boosters - Gartner invented the darn Hype Curve, but now they are seemingly invested in filling it up!
To an extent there is a geneal trend in "rspected" media these days to become more clickbaity - I've noted even such august organs such as the Graniad and Economist are much more prone to this these days, and the "Top 10" Listicle style here is another signal. Does this mean the assumption is no one reads real research unless it's lurid - as one of the comments in the Horses article suggested - imply that:
Or is it something else...
"Perhaps they are spewing off someone else's agenda? #followthemoney"
This second point also links up with something else - from about thetime of the O'Reilly "NextEconomy" conference onwards, I do get the impression the "analyst" and other boosting media of the Tech World has been ordered to get out and push the product as the bubbletime starts to deflate.
The valuation of many Unicorns, current and desired, and all that ride on them may depend on it....
Tuesday, August 30. 2016
Yet another attempt at algorythmic curation of news has failed...Facebook's plans are going back to the drawing board after just a weekend:
Facebook announced late Friday that it had eliminated jobs in its trending module, the part of its news division where staff curated popular news for Facebook users. Over the weekend, the fully automated Facebook trending module pushed out a false story about Fox News host Megyn Kelly, a controversial piece about a comedian’s four-letter word attack on rightwing pundit Ann Coulter, and links to an article about a video of a man masturbating with a McDonald’s chicken sandwich.
That escalated quickly, as they say...not surprised, by the way - judging newsworthiness by what the hoi polloi read is a very risky path to go down. What Humanity is interested in vs what is "News" is a wide chasm.
The automation of curation has been an online dream for at least a decade (we were first asked to work on it in 2007), and has so far failed every time "industrial grade" output is required. But this makes it clear that AIs are still some way from having the smarts to deal with patterm sorting of memes, especially delibeately false and mischievous ones.
The holy grail is getting rid of all the human cost of curation and editing of content, and in other efforts, the human costs of writing it too (for when people stop creating content for no money, maybe?) so that these companies can "Scale" (ie everything is automatable). It's interesting that Facebook initially tried to pretend that it had an algorithm trend finder and was somewhat embarassed when it was revealed that they did in fact need human curation.
If they do get AI curation to "work", then the one prediction I would make is that if the majority of content is machine made from conception to curation, these creators may well find it is also only read by machines Or programmed people.
Friday, August 26. 2016
Apparently Tesla is going to do Solar Roofs as well as Cars:
"Tesla has finalized a $2.6bn deal to buy solar power company SolarCity to produce solar “shingles” – photovoltaic material that would be fashioned into the shape of a house roof."
Elon Musk was quoted as saying:
“I think this is really a fundamental part of achieving differentiated product strategy, where you have a beautiful roof,” Musk said. “It’s not a thing on the roof. It is the roof.”
When I started my consulting career there was a very smart Partner I worked with, and he told me when we first went into a company he looked for 3 signs of about-to-fail businesses, and these were:
- Head Office interiors that had started to look like palaces, he thought it was a sign they were no longer "lean and hungry" and were starting to ossify*
By these measures, Tesla is hitting 2 out of 3 already (I have no idea of their head office palacification) so I know he would be going "Hmmmm...." on this news.
But, while I've always kept his rules in mind, I have found there are some stunning exceptions to these rules that have succeeded - (Apple, Virgin, Nokia for example) - and studying them in depth as to how they do it is fascinating. There seems to be an underlying logic stream to what these companies do and how they do it. Apple enters high potential market segments still saddled with badly integrated and poor UX products and uses its brand to find new customers. Virgin transfers a "cool" brand promise to a previously dowdy and boring consumer segments and makes services more customer friendly. Both have/had extraordinary leaders. Nokia went from tyres to mobile masts to mobiles, so anything is possible, but they have failed at the at the "incredible leader" game for the "next hop" (ditto Apple..?).
So, one possibility is this is F*cked Company time as the Leader jumps from one gambit to another. But arguably, Tesla has an "incredible leader", so what may be a possible underlying logic train here?
As best we can see, it could run something like this - electric cars need a ubiquitous charging infrastructure covering their routes, and that needs to be as cheap to roll out as possible. For people to buy lots of Tesla electric cars a fair portion of this infrastructure needs to exist before they buy them. So how to do that? How about ubiquitous solar roofs that can easily be integrated into a roof-to-charger system (think Fon for car-charging). It's the closest to physical-world game to the internet "increasing returns" one. Even better if its unique to that car company so others can't even use the river without your say so, so how about it being owned by the Car company. And borrowing large wads of money for infrastructure plays has never been cheaper. In essence its a logistics toll play, aka "Castles on the Rhine" - you build your castles first, you get to extract tolls on everyone else or prevent their passage, you win.
Supporting this argument, Tesla is also big time into batteries and has built/bought a factory for them - electric cars need better ones to replace IC cars in all but relativley slow, short duration and low weight tasks right now - but car charging infrastructures using renewable energy also need lots of better batteries so at a stroke there is another huge new market for your batteriees, and they will buy your batteries because you own the roof-to-charger Castle.
The ony problem with building Castles an the Rhine, and building the boats to go on them is that its a very costly thing to do one of these, never mind both, and lots of others will try and do it too. And despite a CEO-as-business-savant, the "F*cked Co" probability ticklist is mounting, so it's going to be an "interesting" one to watch.
In fact, given how hard this two-industry strategy would be to execute, and how costly cars are to make (and that all the major car makers will be in on this game soon), and that Rhine castle owners never really needed to build ships, you do wonder if Tesla should drop cars and do charging infrastructure....plus there is an added benefit - charging stations don't crash and kill people, avoids all that awful bad publicity....
(*Incidentally, one of the things that has interested me over the last 2 decades or so is how much more palatial so many companies' Head Offices have become so if my old Partner was right, there are a lot of ossified businesses out there)
Wednesday, August 10. 2016
Those who have been reading the articles here on the Internet of Things will know that, while we believe the potential is huge, the opportunity for snooping and surveillance is also huge, as is the risk of hacking owing to commercial pressures driving bypasses of good security implementation.
Now, we believe we have found the poster-boy (as it were) for this trend - a personal vibrator that phones home whenever it is used, and that has now been hacked - Grauniad:
To no great surprise.....how was this not predictable? And surely it doesn't need to phone home either, but it does....
The app sends the temperature of the device back to Standard Innovation every minute, and every time the intensity of the vibration changes, that gets sent back too.
Apparently this recording of your comings and goings* is only for "market research" purposes (One wonders if they researched the reaction of people to know that their most intimate experiences were being shared like this). Once upon a time, things like these were made by Spy skunk-works to spy on a few people, now they are made as part of a vast new commercial undertaking to spy on everybody that busy their kit.
Anyway, the hackers have decided to seize the initiative, and launched the “Private Play Accord”, an initiative to encourage sex toy manufacturers to sign up to basic standards of privacy and security. There is no reason why this should no be extended to every Consumer IoT device out there, of course.
We would however bet that the manufacturers will kick back, hard. Because the data they collect is vital for their overall business models, its not just for "market research". That's why just about no IoT consumer device gives you your data, and the option to not make it transferable any farther.
(*yes, it was hard to refrain from using all the puns and double entendre's one could have)
Tuesday, August 2. 2016
Gartner's Technology Trends for 2016 probably contain the most obvious rebottling and labelling of old wine for many a year, probably signalling that the "wave of innovation" of the last few years is coming to an end and its now about making stuff work (and renaming it again).
Here they are, with the Broadstuff summaries characteristically tongue in cheek:
FYI, here is the 2015 Forecast, spot the New Lamps for Old:
As you can see, by and large a smooth continuum except for the new words
Monday, August 1. 2016
Uber has exited China with a sale of all its Chinese operations to the Chinese market leader, for a 17.7% financial stake - Biz Insider:
Uber was burning c $1 billion a year in trying to enter China, a huge cash-hole even for a Megacorn so this helps shore up the cashflow. Downside is that it also closes off Uber's biggest future growth story (see above graph from Biz Insider). But given that market's interesting view of open-ness, its probably a not-bad outcome.
As Biz Insider points out, its a lesson that even infinite bucketloads of VC cash have a limit in what can be done. Still, it will be easier to IPO now, before the investment community works out that Taxis as a business have very low margins.
Also expect to see redoubled efforts in other large and fairly well wired countries where regulators are amenable to having their own domestic taxi industries done over.
Monday, July 25. 2016
System Dynamic model of Brexit (Simplified)
Now that the emotion around the UK Referendum has (hopefully) died down a bit, its time to look at why the (apparently) surprising Brexit result occurred. Based on experience during the referendum campaigns and reading quite a lot afterwards, there were 3 major causes that stood out.
A Mismatch of Belief Systems
In essence, the Remain camp believed an argument based on the EU as a desirable, stable platform going forward, plus the moral and economic benefits of it's precepts, was persuasive. Added to that they clearly felt that Establishment voices of authority would persuade the undecided, and if that didn't work "project Fear" - promising Doom if the UK left the EU, would persuade the floating voters - as they believed it did in the Scottish Independence referendum. (By the way, I think this was false - my recollection was that, at the end, the "Remain in UK" camp in the Scottish referendum made a lot of concessions to the Scots in the last days as Fear wasn't really working out).
Attitude - Hubris and Nemesis, and polls
Before the campaign, Remain was supposed to win, very comfortably, according to the polls. Bookies were offering 1/5 odds on a Leave win. In my view that influenced the campaigns, in that Remain was initially overconfident whereas Leave knew they were in for a real scrap, and as it became clearer that Remain was not going to be a slam dunk then panic set in, whereas Leave grew in confidence. This was exacerbated by the much larger risks to the senior people involved in the incumbent Remain camp.
The System Dynamics of a disaster
However, the biggest failure of the Remain campaign was to not address the situation dynamically as it progressed. The (simplified) System Dynamic diagram above tries to capture this. In essence, Remain's arguments, exaggerated by Project Fear logic, tended to over-egg the risks (or at least be perceived to do so) and that led to an increasing resistance to the message and it gave a foothold to pro Leave media to start to land some telling blows. The Remain response was to double down on Project Fear, with increasingly exaggerated claims of Doom which allowed Leave to both lampoon Remain's claims and headroom to make even more exaggerated claims of its own. Cycle this through a few times, increase the hectoring volume, and more and more people just switched off to the messages of Doom and the insults (calling c 50% of the population "racist" is clearly absurd). As it became clear Leave was gaining, they started to gain in confidence, getting that all important momentum - undecided people like winners. Then Remain visibly panicked, and output became more and more unbelievable (we eventually got to Brexit starting World War 3). By the time the Conservative government, who had largely run the Remain show, started to criticize Labour for not doing enough, it was clear Remain were mortally wounded.
What should Remain have done instead?
This is a simplified model - there are some sub-loops and unique events not shown, but in essence they fit in this overall model. Our experience of System Dynamic models is it is these high level models that often give the major insights, the detail is often bedevilled with layers of assumptions, where anything can happen with small changes. At any rate, the simple model would suggest 5 main actions:
(i) Make sure the ingoing assumptions are all valid, and defendable. GIGO, as they say.
Can we Trump this model?
The main point of making such a model is to see if it is predictive. So we plan to turn it onto the US election, where our hypothesis is that fairly similar dynamics are taking place. So, what we have been doing is following the US election with our systems for a few months to try and calibrate the US systemically, and now the Presidential candidates are anointed we have a simple 2 horse system - and a 2 horse dynamic model to test out on it.
There are differences which we will have to set up for, (for EU read USA, for example) but it should be an interesting experiment (and a decent test of our social analytics systems)
Monday, July 18. 2016
Succinctly put in The Atlantic - (and summarised here), when faced with saying "Yes" to something new, risky, etc, research shows:
“If you are a manager, if you commit a false positive, you are going to embarrass yourself, and potentially ruin your career.” Managers, he says, are terrified of committing false positives, meaning saying something will be a hit when in fact it will flop.
In other words, one is seldom tarred with the results of saying No, and the best way to proect yourself when saying Yes is to only say Yes to "defendable" ideas (worked before, never get fired for buying IBM etc etc)
So, how to avoid this and let innovation flow? The paper argue that peers in an area are the best at judging someone else's work in the space, not managers. (Possibly...but they also say Science advances one dead scientist at a time...)
Anyhow, in most companies, Managers have the Yes/No role and Peers are seldom on tap, so how to get them out of the game theory bind above? The best way is to let Managers act like peers, in an experiment, Justin Berg found that:
"...asked managers to spend five minutes brainstorming about their own ideas before they judged other people’s ideas.” [That] "was enough to open their minds. Because when they came in to select ideas, they were looking for reasons to say no. Get them into a brainstorming mindset first, and now they’re not thinking evaluatively, they’re thinking creatively.”
All very interesting, but if the organisation still kicks you for False Positives, not sure this gets us anywhere further
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