This week’s Top 5 comes from Teo Susnjak a computer scientist specialising in machine learning. He is a Senior Lecturer in Information Technology at Massey University and is the developer behind GDPLive.
As always, we welcome your additions in the comments below or via email to david.chaston@interest.co.nz.
And if you're interested in contributing the occasional Top 5 yourself, contact gareth.vaughan@interest.co.nz.
1. Covid-19 broke machine learning.
As the Covid-19 crisis started to unfold, we started to change our buying patterns. All of a sudden, some of the top purchasing items became: antibacterial soap, sanitiser, face masks, yeast and of course, toilet paper. As the demand for these unexpected items exploded, retail supply chains were disrupted. But they weren't the only ones affected.
Artificial intelligence systems began to break too. The MIT Technology Review reports:
Machine-learning models that run behind the scenes in inventory management, fraud detection, and marketing rely on a cycle of normal human behavior. But what counts as normal has changed, and now some are no longer working.
How bad the situation is depends on whom you talk to. According to Pactera Edge, a global AI consultancy, “automation is in tailspin.” Others say they are keeping a cautious eye on automated systems that are just about holding up, stepping in with a manual correction when needed.
What’s clear is that the pandemic has revealed how intertwined our lives are with AI, exposing a delicate codependence in which changes to our behavior change how AI works, and changes to how AI works change our behavior. This is also a reminder that human involvement in automated systems remains key. “You can never sit and forget when you’re in such extraordinary circumstances,” says Cline.
Image source: MIT Technology Review
The extreme data capturing a previously unseen collapse in consumer spending that feeds the real-time GDP predictor at GDPLive.net, also broke our machine learning algorithms.
2. Extreme data patterns.
The eminent economics and finance historian, Niall Ferguson (not to be confused with Neil Ferguson who also likes to create predictive models) recently remarked that the first month of the lockdown created conditions which took a full year to materialise during the Great Depression.
The chart below shows the consumption data falling off the cliff, generating inputs that broke econometrics and machine learning models.
What we want to see is a rapid V-shaped recovery in consumer spending. The chart below shows the most up-to-date consumer spending trends. Consumer spending has now largely recovered, but is still lower than that of the same period in 2019. One of the key questions will be whether or not this partial rebound will be temporary until the full economic impacts of the 'Great Lockdown' take effect.
Paymark tracks consumer spending on their new public dashboard. Check it out here.
3. Wealth and income inequality.
As the current economic crisis unfolds, GDP will take centre-stage again and all other measures which attempt to quantify wellbeing and social inequalities will likely be relegated until economic stability returns.
When the conversation does return to this topic, AI might have something to contribute.
Effectively addressing income inequality is a key challenge in economics with taxation being the most useful tool. Although taxation can lead to greater equalities, over-taxation discourages from working and entrepreneurship, and motivates tax avoidance. Ultimately this leaves less resources to redistribute. Striking an optimal balance is not straightforward.
The MIT Technology Review reports that AI researchers at the US business technology company Salesforce implemented machine learning techniques that identify optimal tax policies for a simulated economy.
In one early result, the system found a policy that—in terms of maximising both productivity and income equality—was 16% fairer than a state-of-the-art progressive tax framework studied by academic economists. The improvement over current US policy was even greater.
Image source: MIT Technology Review
It is unlikely that AI will have anything meaningful to contribute towards tackling wealth inequality though. If Walter Scheidel, author of The Great Leveller and professor of ancient history at Stanford is correct, then the only historically effective levellers of inequality are: wars, revolutions, state collapses and...pandemics.
4. Bots and propaganda.
Over the coming months, arguments over what has caused this crisis, whether it was the pandemic or the over-reactive lockdown policies, will occupy much of social media. According to The MIT Technology Review, bots are already being weaponised to fight these battles.
Nearly half of Twitter accounts pushing to reopen America may be bots. Bot activity has become an expected part of Twitter discourse for any politicized event. Across US and foreign elections and natural disasters, their involvement is normally between 10 and 20%. But in a new study, researchers from Carnegie Mellon University have found that bots may account for between 45 and 60% of Twitter accounts discussing covid-19.
To perform their analysis, the researchers studied more than 200 million tweets discussing coronavirus or covid-19 since January. They used machine-learning and network analysis techniques to identify which accounts were spreading disinformation and which were most likely bots or cyborgs (accounts run jointly by bots and humans).
They discovered more than 100 types of inaccurate Covid-19-19 stories and found that not only were bots gaining traction and accumulating followers, but they accounted for 82% of the top 50 and 62% of the top 1,000 influential retweeters.
Image source: MIT Technology Review
How confident are you that you can tell the difference between a human and a bot? You can test yourself out here. BTW, I failed.
5. Primed to believe bad predictions.
This has been a particularly uncertain time. We humans don't like uncertainty especially once it reaches a given threshold. We have an amazing brain that is able to perform complex pattern recognition that enables us to predict what's around the corner. When we do this, we resolve uncertainty and our brain releases dopamine, making us feel good. When we cannot make sense of the data and the uncertainty remains unresolved, then stress kicks in.
Writing on this in Forbes, John Jennings points out:
Research shows we dislike uncertainty so much that if we have to choose between a scenario in which we know we will receive electric shocks versus a situation in which the shocks will occur randomly, we’ll select the more painful option of certain shocks.
The article goes on to highlight how we tend to react in uncertain times. Aversion to uncertainty drives some of us to try to resolve it immediately through simple answers that align with our existing worldviews. For others, there will be a greater tendency to cluster around like-minded people with similar worldviews as this is comforting. There are some amongst us who are information junkies and their hunt for new data to fill in the knowledge gaps will go into overdrive - with each new nugget of information generating a dopamine hit. Lastly, a number of us will rely on experts who will use their crystal balls to find for us the elusive signal in all the noise, and ultimately tell us what will happen.
The last one is perhaps the most pertinent right now. Since we have a built-in drive that seeks to avoid ambiguity, in stressful times such as this, our biology makes us susceptible to accepting bad predictions about the future as gospel especially if they are generated by experts.
Experts at predicting the future do not have a strong track record considering how much weight is given to them. Their predictive models failed to see the Global Financial Crisis coming, they overstated the economic fallout of Brexit, the climate change models and their forecasts are consistently off-track, and now we have the pandemic models.
Image source: drroyspencer.com
The author suggests that this time "presents the mother of all opportunities to practice learning to live with uncertainty". I would also add that a good dose of humility on the side of the experts, and a good dose of scepticism in their ability to accurately predict the future both from the public and decision makers, would also serve us well.
18 Comments
Re No.5 .....we all react differently to uncertainty , but you can be sure , we will inherently be more cautious where the variables are unknown or unpredictable
Our upbringing , culture or life experiences all ensure that we have different views and different reactions in uncertain times .
For example , why did some people draw huge amounts of cash from Banks before and during the lockdown ?
Why are some of us taking steps to cut spending ?
Or why are some taking steps to reduce debt like never before ?
Why are some folk in Countdown wearing masks when the staff are not ?
Anyone remember all the hype around Y2K ? .............we expected computers would crash , banks would "freeze" and all manner of stuff would go wrong ..............which turned out to be nonsense .
We will all face change , but we will react differently to the next man , and thats not altogether a bad thing
Not often I agree with you. We can't guarantee permanently broken so long as there is no USA President for Life.
Hegemony: - leadership or dominance, especially by one state or social group over others. The old adage 'when America sneezes the rest of the world catches a cold' may still be true. It is possible to imagine a USA with reduced economic production and an isolationist foreign policy but hard to imagine it losing its dominance in music, fashion from clothes to fast food, TV and film or what might be called 'lifestyle'.
"As the current economic crisis unfolds, GDP will take centre-stage again and all other measures which attempt to quantify wellbeing and social inequalities will likely be relegated until economic stability returns".
The floggings will continue until morale improves.
All passengers will refer to the current data on carpet-drying. Signed - Capt, Titanic.
Sorry, but it sounds like self-justification to me. We should really be pointing out that 'economic stability' is - if you were measuring properly - well in the rear-view mirror. Did you factor the planetary Limits to Growth into your code, Teo? Were you taught that there are physical and biological limits? Have you ever looked at WORLD3, and it's updates/reviews? Though of integrating it into your GDP stuff? (hint - you'll find World3 will be the dominant feature).
I appreciate that the majority will indeed attempt to go back to what they were doing, but that collectively was peaking and about to fall off an increasingly steep cliff. The virus was a trigger event, not a stand-alone hiccup. Please factor the real planet into your constructs; failure to do so will always relegate predictions to tea-leaf-reading status. Stock-measurement rather than flow measurement is probably a key starting-point.
And factoring in fact(s) tends to reduce the amount of uncertainty one needs to live with......
I don't get your climate reference; it seems to me the wisdom of multiple posits seems to be tracking fairly well. But Climate Change is merely the exhaust of our energy-use, which in turn is a result of work being done. Again, you have to read whole systems to make sense of the way problems mesh and with what weighting.
https://www.forbes.com/sites/startswithabang/2017/07/26/heartlands-6-re…
This briefly addresses the climate change graph. There's newer and better data suggesting the models more closely match observations.
I suppose I'm committing a guilt by association fallacy here, but I can't help but notice that the author of the first graph is known as a creationist as well as a climate denier.
It's quoting reality, there is some truth that well-being and social inequalities get paid for through economic performance, whether they are internal or international. That's not to say that others don't over-consume.
It links to Maslow, in terms of immediacy: Feed people securely, make them physically safe, and then they will progress to other levels. At that point, they look beyond to climate or equity/equality/social justice - whatever the title people want to give it.
Whether the economic system is "right" is debated strongly, I'm not judging, just pointing out that for people to consider alternatives, they have to be physically and emotionally ready. In the middle of Pandemic and mass unemployment, probably not, and governments are unlikely to make change that stops their people getting fed, the electoral cycle would see to that.
The AI bit on tax policy is fascinating, even with it's identified limitations. Middle income earners have the lowest tax rates. Incentives and benefits to lift the most. now how to create the jobs, in the regions to enable such a model applicable? Or do we all have to move to Auckland to empty their water reservoirs faster?
Very cool Top5.
I got #4 right in guessing that I was talking to a bot. Interestingly, I asked Are you a bot? And it said 'ya'.
#5 Sheila Jasonoff talks about predictive models being 'technologies of hubris' and calls for scientists to employ 'technologies of humility';
https://www.nature.com/articles/450033a
Regarding #5: https://www.forbes.com/sites/startswithabang/2017/07/26/heartlands-6-re…
The so-called data line on that graph was wrong. But I'm sure you wouldn't believe a lefty rag like Forbes... :)
And I am a modeller - they are compelling but not foolproof, and often just serve to point you towards what better data you need to collect to really understand things.
#5 - the key part to this Interesting Top 5. Humility is what's needed, in large doses. But the zeitgeist does not reward that (and possibly never has), so we are stuck with 'experts' making predictions which politicians act on and populations that are scared into following. And the kudos that results reinforces the loop....plus the catastrophiles amongst us amplify the scares, and that engenders More Research and More Scary Predictions....
A local example: thousands of Christchurch coastal properties have LIM's associated to their titles which Predict Dire SLR. But, and quietly, and recently, a NIWA study and review comes to a rather saner conclusion:
In the eternal balance between local shoreline accretion via river-transported sand accumulation and longshore drift, versus historical SLR - a thousands-of-years shoreline advance - we are safe until at least 2120...... but good luck to seeing them LIM's withdrawn.....
#1 - the focus is mainly on demand, sales and logistics measurement and prediction systems, which have a very strong recency bias and limited exposure to spikes, as the article admits. Whether this constitutes 'AI' in anything but a very limited form is debatable.
“You need a data science team who can connect what’s going on in the world to what’s going on the algorithms,” he says. “An algorithm would never pick some of this stuff up.”
Which is where the notion of collecting 'the wisdom of crowds' from such reliable sources as Twitter, FB or - shudder - Interest comment threads is referred in the source article in - shall we say - Hushed Tones.
Upset the AI ay? All the signs are showing us that we have entered the cusp of our age. The huge ups & downs of the markets, the tussle over ''good & bad'' information via media & other sources, the generally poor health (& attitudes) of our younger generations, the obvious angers out & about there, the embarrassing leaderships over the past decade (or more) & the related generally poor state of the state apparatus itself - global, regional, national & local, the deliberate splitting of our culture into the left & the right which makes for a divided societies/communities & even the pandemics which upset the computer AI predictions of FMCG & other items of necessity, as we try to go about our daily lives. They are all signs of huge change.
To watch & be part of a society in decline is not my ideal life choice, but it still beats being shipped off to a war, as a younger man, to the other side of the planet, like my father was & his father was before him, to fight & die for something that was worth fighting for, or so we thought at the time. What those men fought & died for is still as important today as it was then, it's just that we've forgotten about that to a larger extent & probably even worse, taken it for granted, which has led to today's divisions (look at the state our families) when indeed, what we (still) have on offer today is the best life choice on planet earth today. That's why almost everyone else wants to come & life here, & while those that don't, hate us & want to close us down (read destroy). And this is my point: Those bad actors like China, Russia, Iran, Turkey & the like, are actively targeting & indeed destroying the freedoms of the West quite effectively through their bots, through our own media, on our own computers, whilst at the same time behaving in an even worse fashion to their own people. Do not believe anything you see or hear on the media until you've read or heard the other side of the story. Why? Because the media only want to tell/show you one part of the story, not the whole story. In fact I believe this to be a truism of all forms of media. They are perhaps, the source of the true cancer within our culture in decline.
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