21st century economics to ditch physics; Amazon’s leadership. Cambridge Analytica; Algorithmic management and the failure of decency; AVs and the insurance dilemma; Uber losses; Power market turned upside-down; Human heart grows on spinach leaves; Water solidified at boiling point.
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Dept of the near future
💭 Jeff Bezos’s letter to Amazon shareholders. “Day 2 is stasis. Followed by irrelevance. Followed by excruciating, painful decline. Followed by death. And that is why it is always Day 1.”** COMPELLING**
🔫 We need alternatives to Facebook, argues Brian Bergstein.THOUGHTFUL (See also: ”the use of Facebook [is] negatively associated with overall well-being“ argue Shakya & Christakis in HBR.)
🍩 Kate Raworth on doughnut economics. Traditional economics is based on a fallacy, the most pernicious legacy of this fake physics. Instead, we need dynamic, systems approaches. EXCELLENT (See also EV#19 on biologically-inspired economics.)
📣 EV reader, Fred Wilson: We need more decentralised, self-organizing systems.
🖇️ Why people may prefer unequal societies. ”[P]eople have an aversion toward unfairness [which often] leads them to favour unequal distributions. [We should] focus not on whether the [distribution of wealth] is viewed as fair.“ INTERESTING (Long-ish academic paper.)
🗳️ Paul-Olivier Dehaye’s presentation on Cambridge Analytica, personal data and electioneering is a MUST READ.
Dept of algorithmic management
One element of the United Airlines story intrigues me: how firms start to rely on process so heavily that it becomes an excuse for eliminating employee discretion, common sense or kindness. We know that in the recent case, United didn’t follow its processes exactly but the incident demonstrates the fundamental issue of processes debilitating decency. It’s a small example of the risks of algorithmic management.
John Robb sums it up in this EXCELLENT essay:
The entire process was inevitable. It’s also not a unique situation. We’re going to see much more of this in the future as algorithms and authoritarianism grow
To which I’ll add that while the passenger’s treatment resonates viscerally, we are all, as consumers and citizens, at the mercy of black-box processes (aka algorithms). When we engage with business and government and are fed through a decision tree. When an insurance claim is processed. When we are triaged by a telenurse. When we make a complaint. These are often rigid black-box systems.
The humans operating these processes in many cases have limited discretion. This discretion has been whittled away over years in the name of optimisation or standardisation. And in many cases, that process has led to efficiency, fewer errors and higher quality for us.
But in some instances (especially with quasi-monopolists) a black-box culture that is irredeemably inflexible and opaque. In many industries, the human is already out-of-the-loop, simply following a script. We’ve all heard an agent say “the system doesn’t allow me to do that.”
Will automated systems make this more or less common? The silver lining is that they could be less brittle than current processes. A machine learning system could learn rapidly from experience, ultimately optimising more efficiently and with greater efficacy that an ‘architect-once, implement forever’ process manual. Human overseers could have the power to override such genuinely automated systems if the machines suggest macabre outcomes.
The risk is the opposite will happen because firms will expediently implement poorly designed ones with little consumer redress or business impact.
Dan Hon has an amusing tweetstorm that plays out this management calamity.
- Enrique Dans: The future is what it is: the continuing development of ever-better technologies able to help people work with them.
- Interview with a US grad student who spent the summer making iPhones in a Chinese factory. FASCINATING. (The division of labour seems to be perfected. #evilcackle.)
- The robot wars in American factories.
- We need new economic tools to measure the impacts of automation in the economy. (Although the author refers to the success of econometrics in this piece, which complexity economists and systems thinkers might challenge. See the doughnut economics at the top of this newsletter.)
Dept of artificial intelligence
Will Knight on the challenges of making artificial intelligence explainable and the progress we are making to do so. EXCELLENT READ
Neural networks made easy. Nice, non-technical introduction.
Accessible & fun history of dueling neural nets.
Nate Soares on ensuring smarter-than-human intelligence has a positive outcome. (Long read.)
Small morsels to appear smart at dinner parties
Human heart grown on spinach leaves. (Thanks to my son for finding this.)
🗑 Are you a fan of Trump board game, Coca-Cola BlāK or Peek? They’re displayed in the Museum of Failure.
Neuroscientists are rethinking the rules of memory.
108 years of university graduate facial hair styles. 👨🎓Beards, ahoy.
🌞 Solar and wind now the cheapest power globally.
Male justices interrupt female justices 3x as often as they interrupt each other.
🍼 Infants show racial biases even at six months.
Fear of diversity made more people vote Trump.
Index funds beat active managers 92% of the time.
Several of you asked about commenting on stories we feature.
We’re experimenting on how we might do this. Today, we’re suggesting you tweet with the hashtag #ev109, perhaps related to algorithmic management (or something else). Let’s see how it works.
It’s the Easter public holiday in the UK, so we have a few days here. If you have some time off, I hope you are making the most of it too.
P.S. 🔥 Our twitter handle is still on fire. You should follow it.
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