The Age Of Conspicuous Thrift Returns With A Vengeance

A decade ago, amidst the echoes of the global financial crisis, we were talking about a new Age of Conspicuous Thrift and the 'counter-Veblen effect' when "preferences for goods increase as their price falls, over and above the traditional supply and demand effect, due to a conspicuous thrift amongst some consumers." A week ago, it was pointed out there are more food banks than McDonalds outlets in the UK. And a survey by Mazuma Mobile, the mobile phone recycling firm, has found that 85% of Brits regularly purchase pre-owned products instead of new, from books and handbags, to computers and mobile phones. In fact, 45% plan on giving pre-owned items as gifts this Christmas and 52% would happily receive them.

Over the past decade we've had very low interest rates, plenty of cheap credit, £36bn in PPI compensation (though some is yet to be paid), strong employment and some feeble growth, yet UK household debt remains at record levels and the UK economy is shrinking. That means 2020 is set to be a very hard year, which explains why so many Brits are battening down the hatches - particularly those in the early stages of their careers. Previously, those aged 25 – 34 were most likely to purchased pre-owned items as gifts, but they've been overtaken by 18 – 24 year olds. 

Londoners (60%) and the Northern Irish (66%) are happiest to receive pre-owned items as presents, yet even the lowest figure is still 43% (in the North West), which means conspicuous thrift, rather than conspicuous consumption has really taken hold in the UK. 

Craig Smith from Mazuma Mobile says: 

“Attitudes are changing towards pre-owned shopping as people become savvier with their cash...  many of us are simply happy to receive something we like, especially when it’s better for the environment and our wallets. In fact, over a third of those we surveyed (37%) said they would consider having an entirely pre-owned Christmas this year, including gifts and decorations!"

The top 10 pre-owned items purchased among the 2,000 people surveyed by Mazuma Mobile via OnePoll in October 2019 were:

1. Books (68%) 

2. Cars (62%) 

3. Furniture (49%) 

4. Clothes (43%) 

5. Jewellery (37%) 

6. Musical instruments (35%) 

7. Mobile phones (34%) 

8. Televisions (32%) 

9. Handbags (29%) 

10. Computers (29%) 

It's Time To Focus On Johnson's AltRight And Russian Links

With Boris Johnson desperate for a quick General Election, it's important to be aware that the Trump Presidency is simultaneously unravelling over links with Dmitry Firtash, securities fraudster Lev Parnas and the mob and the British authorities are reported to have their own concerns about some of Johnson's relationships. The legality of these need to be clarified if we are to have any chance of avoiding another election featuring fake news and dodgy funding, though Facebook isn't proving helpful either...

Johnson's links with Trump's AltRight pals include Steve Bannon and the Breitbart Boys - like Trump's speechwriter and rally fluffer, Stephen Miller. Bannon has advised Boris Johnson, among other European right wing political party leaders. And Miller attended the Innotech Summit hosted by Johnson's pole-dancing "friend" Jennifer Arcuri, whose links with Johnson are also the subject of investigation. Matthew Elliott chaired Johnson's Vote Leave campaign, and brings an array of AltRight contacts and funding links.

Johnson has also been linked to Russian tycoons Lebedev and Temerko, while Tory Brexidiots and Vote Leave's campaign director and Johnson adviser, Dom Dum Cummings, have long-standing ties to Dmitry Firtash - the same Ukrainian 'oligarch' at the heart of Trump's attempt to lift sanctions imposed on Russia for its invasion of Ukraine and for the Ukrainians to publicly investigate his 2020 campaign opponent - for which Trump is now being impeached.

That's also important because Vanity Fair recently reminded us that:

"...Trump called Johnson on July 26, two days after the new U.K. prime minister took office, apparently to ask BoJo for help compiling evidence to undermine the investigation into his campaign‘s ties to Russia. For those of you keeping up at home, that’s just one day after Trump spoke to Ukraine President Volodymyr Zelensky and asked for “a favor...”

Note that US Republicans consider that donations arranged by Trump henchman Lev Parnas are so dodgy that they were simply returned.

All of this also makes you wonder again where Arron Banks' £8m donation to the Leave cause might have ultimately came from... even if it was not unlawful.

And with Fakebook determined not to police political advertising and yet to admit any wrongdoing to the UK's Information Commissioner over Cambridge Analytica, we could well be in for another dodgy British election.

Do You Know You Are Using And/Or Exposed To Artificial Intelligence?

Source: datamation

Amid the news that the Department of Work and Pensions is using artificial intelligence to decide benefits claims, a third of UK financial firms recently told the Bank of England and Financial Conduct Authority they were not using 'machine learning' (a subset of AI) in their businesses. That's pretty concerning, given the kind of AI we all use without realising and the fact that anyone wrongly denied benefits will need short term finance. That response also begs the question whether those firms know how their many stakeholders are using AI (whether unwittingly or not). If their suppliers, intermediaries, customers, investors, competitors and the government are using AI, then how does that affect their own strengths, weaknesses, opportunities and threats? And how does that in turn affect their stakeholders? No city on Earth is ready for the disruptive effects of artificial intelligence. Also worrying is the finding that smaller, fintech firms seem to believe that machine learning is no use to them. And given the problems with AI explained below, it's important for everyone to consider whether and how they rely on or are otherwise exposed to the two thirds of financial firms who are actually using AI... hyping the benefits without understanding the shortcomings will harm our trust AI where it could be helpful.

What is AI?

The term "AI" embraces a collection of technologies and applications, with machine learning usually featuring at some point:

• narrow artificial intelligence
• machine learning
• artificial neural networks 
• deep learning networks 
• automation
• robotics
• autonomous vehicles, aircraft and vessels
• image and facial recognition
• speech and acoustic recognition
• personalisation
• Big Data analytics

At the recent SCL event I chaired in Dublin, Professor Barry O'Sullivan explained that AI technologies themselves may be complex, but the concepts are simple. In essence, machine learning differs from traditional computer programming in that:

• traditionally, we load a software application and data into a computer, and run the data through the application to produce a result (e.g. how much I spent on coffee last year);

• while machine learning involves feeding the data and desired outputs into one or more computers or computing networks that are designed to write the programme (e.g. you feed in data on crimes/criminals and the output of whether those people re-offended, with the object of producing a programme that will predict whether a given person will re-offend). In this sense, data is used to ‘train’ the computer to write and adapt the programme, which constitutes the "artificial intelligence".

What is AI used for?

AI is used for:

1. Clustering: putting items of data into new groups (discovering patterns);
2. Classifying: putting a new observation into a pre-defined category based on a set of 'training data'; or
3. Predicting: assessing relationships among many factors to assess risk or potential relating to particular conditions (e.g. creditworthiness).

The Challenges with AI

The primary concerns about AI relate to:

1. cost/benefit - $50m in electricity to teach an AI to beat a human being at Go, hundreds of attempts to get a robot to do a backflip, but it can't open a door;
2. dependence on data quantity, quality, timeliness and availability;
3. lack of  understanding - AI is better at some tasks than humans (narrow AI) but general AI (same as humans) and superintelligence (better than humans at everything) are the stuff of science fiction. The AI that can predict 79% of European Court judgments doesn't know any law, it just counts how often words appear alone, in pairs or fours;
4. inaccuracy - no AI is 100% accurate;
5. lack of explainability - machine learning involves the computer adapting the programme in response to data, and it might react differently to the same data added later, based on what it has 'learned' in the meantime; 
6. the inability to remove both selection bias and prediction bias - adding a calibration layer to adjust the mean prediction only fixes the symptoms, not the cause, and makes the system dependent on both the prediction bias and calibration layer remaining up to date/aligned over time; 
7. the challenges associated with the reliability of evidence and how to resolve disputes arising from its use; and
8. there's a long list of legal issues, but lawyers aren't typically engaged in development and deployment.

This means the use of AI cannot be ignored. We have to be careful to understand the shortcomings and avoid hyping the benefits if we are to ensure trust in AI. That means challenging its use where the consequences of selection bias or false positives/negatives are fatal or otherwise unacceptable, such as denying fundamental rights or compensation for loss.

Instead, artificial neural networks and deep learning are better used to automate decision-making where "the level of accuracy only needs to be "tolerable" for commercial parties [who are] interested only in the financial consequences... than for individuals concerned with issues touching on fundamental rights."

Being realistic about AI and its shortcomings also has implications for how it is regulated. Rather than risk an effective ban on AI by regulating it according to the hype, regulation should instead focus on certifying AI's development and transparency in ways that enable us to understand its shortcomings to aid in our decision about where it can be developed and deployed appropriately.

The Conspiracy Theory Of Conspiracy Theories

I'm fascinated by conspiracy theories, and just happened across the Daddy. Corey Doctorow, the entertaining science fiction writer, believes he's found the source of them all:

"... [conspiracy theories] aren’t attributable to ideology or mind-control rays... at root, they are a disagreement about how we know whether something is true or not. When we argue about the flat Earth, we’re not just debating the shape of our planet: We’re debating the method by which we can know its shape....40 years of rising inequality and industry consolidation have turned our truth-seeking exercises into auctions, in which lawmakers, regulators and administrators are beholden to a small cohort of increasingly wealthy people who hold their financial and career futures in their hands. Industry consolidation makes it startlingly cheap to buy the truth: Once an industry consists of a handful of players, it’s easy for everyone to agree on the play, and the only people qualified to be referees are drawn from the companies’ own executive ranks, whence they will return after their spin in governance’s revolving door."

Not only is this thesis merely political hogwash designed to justify a call to break up certain industry oligopolies, but it also serves to highlight how the human brain works to make conspiracies attractive in the first place (as explored by Nobel prize-winner Daniel Kahneman and Nicholas Taleb, often mentioned here). 

The central problem is 'overconfidence' - the belief that our existence is somehow 'controlled' rather than random (also at the root of creationism vs natural selection, for example).

I mean, just imagine if all the data that every human perceives really were "bought" or curated by "a handful of players" - let alone after only 40 years of trying...

A moment's thought, let alone a cursory read of James Gleick's excellent history of humanity's attempt to master information reveals this would not be possible. And many different conspiracy theories abound in the many different communities around the planet.

Even complaints about deliberate misinformation causing the outcome of specific votes, like Brexit, are overdone. As Taleb points out, such outcomes may be classified as Black Swans - surprise events that we try to rationalise by hindsight. Lies and misinformation might be part of the swirl surrounding Brexit, yet may really only correlate with the result without being causative - they could be just as symptomatic of a deeper malaise as the result of the vote itself. 

That's not to say lies and electoral violations should be overlooked or go unpunished - or that we should not try to rectify obvious economic mistakes or life-threatening misconceptions like the "Anti-Vax" movement. But ultimate 'control' just isn't an option. We can only minimise our exposure to the downside, and maximise our exposure to the upside, of the major events that shape our history.

Applying that to Doctorow's theory: the break of up of industry oligopolies may be worthwhile for certain reasons, but that process will not somehow restore human control over the 'truth' - any more than it will alter human psychology.

Why Suggest A Bridge Between Scotland and Ireland?

Popularity develops through the snowball effect and the bandwagon effect. Some things or people are popular because they're useful, solve a real problem or are widely appreciated for some intrinsic quality: the wheel, a rock song/group, the telephone...  But what if you have nothing genuine to offer? How do you create your own snowball and bandwagon effects out of thin air? 

You do what every snake oil salesman in the Wild West did, what Bernie Madoff did, what every religious sect leader has done, what reality TV show producers do - and what the likes of Farage, Johnson and Gove have done...

You create or 'boost' something hugely ambitious, unique, deceptively simple, vaguely plausible but not actually 'real' in the sense of being achievable or demonstrable. Something in which your victims can only have faith.

Committing to solve a really big, actual problem is out of the question. Firstly, it's really hard and will take a long time, because it involves changing actual behaviour and fighting inertia - the resistance to change. Secondly, it won't make you exclusively popular because you'll likely be competing with lots of others trying to solve the same problem. You won't stand out in the crowd. You won't capture peoples' attention.

And real problems won't capture your followers' imagination or their faith.

To make your victims cling to their belief for a long time, you also need a goal that’s really big and ambitious - because, if they go for it, a big project will commits lots of people, money and resources that can't easily be redeployed.

And if the goal isn't 'real' it can never quite be achieved or delivered or found (think the Holy Grail): the quest is never-ending. Once you’ve got your popularity snowballing it's just about the journey, not the destination. Nobody wants to stop believing (and spending). Negotiating trade deals is an endless process - the job of leaving the EU successfully will literally never be "done". There's no easy way to leave the cult. Inertia is now on your side!

Here are some examples of projects that were or are hugely ambitious, deceptively simple, vaguely plausible but not actually achieved or achievable that seem to have been conjured up to boost someone's popularity... You'll see that Johnson's proposal for a bridge between Scotland and Ireland fits right in - get that feasibility study started!

• an airport in the middle of the Thames;

• long term stock market returns of 11% (not the widely accepted 8%);

•  Farage's decades long quest for Britain to leave the EU;

• the 'Leave' campaigns, as backed by Johnson/Gove and Farage/Banks;

• the garden bridge;

• donate X% of your income for eternal salvation;

• build a bridge between Scotland and Ireland. 

And finally, a word from the perpetrator of the biggest fraud of all time... (or is it?)...