A couple of years ago I went on a three day trek that all but shattered my love of hikes. It was a hilly circuit, slippery and hot. But on the third day, as we slowly ran out of lollies, food, patience and even water; we were repeatedly greeted by false summits.
The successes of deep learning have been truly remarkable and have caught many of us by surprise. Nevertheless, deep learning has succeeded primarily by showing that certain questions or tasks we thought were difficult are in fact not. It has not addressed the truly difficult questions that continue to prevent us from achieving humanlike AI.
Artificial Intelligence has famously had a few “winters”, as what seemed like fundamental breakthroughs petered out. Similarly, the list of “transformational” technologies that failed to make a real dent is incredibly long.
For the non technical among us it can be very easy to mistake these kinds of false summits for fundamental transformation. Especially as they often do represent some progress. Finding themselves in products that we actually use or glimpse on breakfast television etc.
Part of the problem is framing. Especially as the incentive for so many is to hype. But it’s also a focus on outcomes rather than process.
The torture of that trek came from us focusing on the end rather than the journey. We lost track of the scenery, fresh air and each other.
We get tricked by technological false summits in the same way. By focusing so intently on what the technology can do. But the real power comes from looking at the process. Both the roadblocks and potential from questioning what the difficult questions are.
As always my emphasis
The history of human progress is often viewed through significant events, movements and achievements. But what if we look at it as a story of how we think about the world?
Counterfactuals are the building blocks of moral behavior as well as scientific thought. The ability to reflect on one’s past actions and envision alternative scenarios is the basis of free will and social responsibility. The algorithmization of counterfactuals invites thinking machines to benefit from this ability and participate in this (until now) uniquely human way of thinking about the world.
I came across these sections in the early parts of The Book of Why by Judea Pearl. It’s a book on the science of causality. Here he’s exploring some of the differences between humans and the current crop of “thinking machines” – artificial intelligence and other algorithmic “learning” from data.
I’ve always loved counterfactuals as a rhetorical device, sort of a stripped down model. We can play with what if’s and construct something together. Try to tease out causality and significance, however elementary.
But it’s interesting to consider this as a driver of human evolution. As a methodology for iteration that doesn’t appear to be possessed by other animals or modern computer models.
Within 10,000 years after the Lion Man’s creation, all other hominids (except for the very geographically isolated Flores hominids) had become extinct. And humans have continued to change the natural world with incredible speed, using our imagination to survive, adapt, and ultimately take over. The advantage we gained from imagining counterfactuals was the same then as it is today: flexibility, the ability to reflect and improve on past actions, and, perhaps even more significant, our willingness to take responsibility for past and current actions…
Many of us have a tendency to favour the concrete and eschew the hypothetical. But risk aversion, imagination and learning from experience – among other drivers of progress – by necessity recognise the possibility of other outcomes. They are built on counterfactual thinking.
And, maybe more interestingly when we compare human intelligence to that which we try to create, it may be somewhat innate?
…Counterfactual reasoning, which deals with what-ifs, might strike some readers as unscientific. Indeed, empirical observation can never confirm or refute the answers to such questions. Yet our minds make very reliable and reproducible judgments all the time about what might be or might have been. We all understand, for instance, that had the rooster been silent this morning, the sun would have risen just as well. This consensus stems from the fact that counterfactuals are not products of whimsy but reflect the very structure of our world model.
As always my emphasis
Low overhead + “do what you love” = a good life.
“I deserve nice things” + “do what you love” = a time bomb.
I’ve completely overhauled my life in the past couple of years, trying to minimise unnecessary or extravagant expenditures and commitments. I had allowed lifestyle inflation to trap me in a situation where I had to earn a certain amount. I had fallen for the advertiser’s vision of freedom and empowerment through consumption, rather than a financial, emotional and mental freedom to work on things that have impact and bring me joy.
I don’t know how I got there, as I used to break consumption down into its time value. Calculating how many hours in my minimum wage job equated to getting a couple of pizzas delivered, for instance.
I seem to have stopped this at some point, but it’s a remarkably effective way of identifying what’s worth the trouble. I came across a very stark illustration today in The Art of Frugal Hedonism:
how fast does your car really go, on average? We’re not alluding merely to time stuck in traffic here. To truly calculate the ‘effective speed’ of our vehicles we need to include all the hours we put in at the office to cover fuel, registration and other running costs… with that speedometer sitting right on zero all the while. One Australian study calculates that for every hour spent driving a Toyota Landcruiser, the average owner spends another 1.5 hours working to pay for it. The study also points out that if the owner had to pay for their car’s ‘externalities’–those costs borne by society–of CO2 emissions, traffic congestion and the cost of road accidents, they’d need to work another 0.6 hours for every hour behind the wheel. That puts the effective speed of a Landcruiser at 9 kilometres (5.7 miles) per hour. Not so convenient after all, eh? A bicycle, by the way, with its far lower purchase, running, and externality costs, clocks in at a relatively speedy 18 kilometres (11 miles) per hour.
You could probably run similar analyses on almost any gadget or service that supposedly saves you time or adds convenience.
I, most of us probably, take our work lives as given. We must work full time. That gives us X dollars. Then we use those dollars as best we can to maximise the non-work hours.
But what if you reversed this? Every minute you save by owning a car (could be anything) is one you pay for with one or more minutes at work. Could you do without the car and simultaneously reduce the work? How convenient is the gadget in terms of the hours required to pay for it, purchase it, maintain it and eventually replace it?
What if you rethought both the numerator and the denominator?
As usual my emphasis
- Would you survive a merger with ai?
- Ivanka trump’s fight for the trump dynasty
- The ghost towers of Iran’s housing crisis
- India and the great divergence: an Anglo-Indian comparison of gdp per capita, 1600–1871
- The tweety bird test
- Dropshipping journalism
- African countries are missing the data needed to drive development($)
- Inside the phone company secretly run by drug traffickers
- Age of invention: rise of the mathematicians
One of my major issues with modern, broadcast journalism is its normalisation of a one dimensional view of accuracy. When called out over a questionable story the retreat mostly takes place to the “facts” within the story itself. Solace is found in the precise sourcing of a story, even if that isn’t the way knowledge actually works.
Rarely are other dimensions questioned, such as whether the story’s very existence is misleading or lends undue credence or salience. Because that, also, is inaccurate. The five stories every day on petty crimes may be exact in recounting the details (as far as we can ever know), but is the presence of five stories an accurate portrayal of the magnitude of the problem?
Is this conflating precision with accuracy?
…precision can mask inaccuracy by giving us a false sense of certainty, either inadvertently or quite deliberately.”
This is from Naked Statistics by Charles Wheelan. I’m about halfway through and haven’t come across much that would be surprising to anyone who has done an intro statistics course. But Wheelan has an interesting way of theorising what are otherwise mundane concepts.
Consider his framing of “precision” and “accuracy” (forgive the long quote):
These words are not interchangeable. Precision reflects the exactitude with which we can express something. In a description of the length of your commute, “41.6 miles” is more precise than “about 40 miles,” which is more precise than “a long f——ing way.” If you ask me how far it is to the nearest gas station, and I tell you that it’s 1.265 miles to the east, that’s a precise answer. Here is the problem: That answer may be entirely inaccurate if the gas station happens to be in the other direction. On the other hand, if I tell you, “Drive ten minutes or so until you see a hot dog stand. The gas station will be a couple hundred yards after that on the right. If you pass the Hooters, you’ve gone too far,” my answer is less precise than “1.265 miles to the east” but significantly better because I am sending you in the direction of the gas station. Accuracy is a measure of whether a figure is broadly consistent with the truth—hence the danger of confusing precision with accuracy. If an answer is accurate, then more precision is usually better. But no amount of precision can make up for inaccuracy
Bringing this back to journalism, it highlights the fallacy in retreating to details rather than the bigger picture. If a portrayal of the world is an accurate one then precision is laudable. But you can’t sacrifice one for the other. By no means conflate one with the other.
If the audience walks away with all the details of the criminals but a misleading impression of the likelihood of their being a victim, that’s a failure. And it’s one we all eventually pay for through public policy.
This is a rabbit hole I’ve wandered down many a time when thinking about journalism and the possibility of representing truth. Whether achievable or not, truth definitely isn’t entirely in the details.
As usual my emphasis